WO2021043014A1 - 基于生物特征的身份认证方法及其身份认证系统 - Google Patents

基于生物特征的身份认证方法及其身份认证系统 Download PDF

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Publication number
WO2021043014A1
WO2021043014A1 PCT/CN2020/110740 CN2020110740W WO2021043014A1 WO 2021043014 A1 WO2021043014 A1 WO 2021043014A1 CN 2020110740 W CN2020110740 W CN 2020110740W WO 2021043014 A1 WO2021043014 A1 WO 2021043014A1
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Prior art keywords
mobile terminal
numbers
base station
user
terminal number
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PCT/CN2020/110740
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English (en)
French (fr)
Inventor
余玮琦
万四爽
何朔
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中国银联股份有限公司
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Priority to JP2021576570A priority Critical patent/JP7204016B2/ja
Priority to US17/620,850 priority patent/US11811756B2/en
Publication of WO2021043014A1 publication Critical patent/WO2021043014A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
    • H04L63/0861—Network architectures or network communication protocols for network security for authentication of entities using biometrical features, e.g. fingerprint, retina-scan
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/172—Classification, e.g. identification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/761—Proximity, similarity or dissimilarity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/803—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of input or preprocessed data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1365—Matching; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/14—Vascular patterns
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/70—Multimodal biometrics, e.g. combining information from different biometric modalities
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3236—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/06—Authentication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/60—Context-dependent security
    • H04W12/63—Location-dependent; Proximity-dependent
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/60—Context-dependent security
    • H04W12/63—Location-dependent; Proximity-dependent
    • H04W12/64—Location-dependent; Proximity-dependent using geofenced areas
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/60—Context-dependent security
    • H04W12/69—Identity-dependent
    • H04W12/72—Subscriber identity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences

Definitions

  • the present invention relates to computer technology, in particular to an identity authentication method based on biological characteristics and an identity authentication system based on biological characteristics.
  • Face recognition technology is developing rapidly, and the technology maturity has basically met the requirements of financial applications for recognition accuracy and recognition efficiency, and it is mostly used in payment and public security scenarios.
  • iPhone X launched the Face ID function
  • Alipay piloted face-swiping payment and the Agricultural Bank launched face-swiping withdrawals.
  • Face recognition technology is becoming one of the most rapidly developing biometric technologies with the broadest application prospects.
  • face recognition can be divided into two types, namely 1:1 and 1:N, according to the number of recognition ranges.
  • 1:1 means that in the recognition process, the face information in the sample picture is known, and the recognized picture is compared with the known sample face photo to determine whether it is the same face in the photo.
  • 1: N means that in the recognition process, there is a face sample library, there are N sample photos in the library, the recognized face photos are compared with the samples in the library, and it is recognized that the face image belongs to a certain sample in the library .
  • 5G technology is also a hot technology in the past two years.
  • the deployment of base stations in the 5G era will be a combination of outdoor "macro base stations" and multiple indoor “small base stations”.
  • Small base stations have the characteristics of limited signal coverage area, easy deployment, self-optimization and low cost, and will be the backbone of indoor scenarios in the future.
  • the operator can know the mobile phone number of the user accessing the small base station. Using this feature, in cooperation with the operator, a face recognition method based on the 5G base station can be formed.
  • the current 1:N face recognition mainly has three modes:
  • the first is face recognition in a closed environment, such as a campus, a small area such as a campus, and an environment where N is controllable and has a fixed upper limit.
  • the second method is to reduce N through auxiliary methods.
  • the face recognition of Alipay requires the user to enter the last 4 digits of the mobile phone number to reduce N.
  • the third is to obtain the user's mobile phone number and corresponding location information through the 5G base station, and then according to the user's commonly used historical location information, the user's facial features are sent from the cloud database to the edge node closest to the user's commonly used historical location Save it.
  • the edge node closest to the user's commonly used historical location Save it.
  • the fourth is to register the face and the Bluetooth mac address of the mobile phone when the user registers.
  • identifying turn on the Bluetooth function of the mobile phone, and reduce the range of N through the mac address accessed by the merchant.
  • the first mode limits the scope of use of face recognition. Face recognition cannot be achieved in some open scenes such as supermarkets and restaurants.
  • the Bluetooth function is not a frequently used function of the user, which is equivalent to requiring the user to perform an additional opening operation, and the user experience is poor.
  • the present invention aims to propose a biometrics-based identity authentication method and a biometrics-based identity authentication system that can accurately realize identity authentication in an open environment.
  • the identity authentication method based on biological characteristics of the present invention is a method for identity authentication based on the biological characteristics of the user and the mobile terminal carried by the user, and is characterized in that it includes the following steps:
  • the step of generating a first mobile terminal number list is to obtain the mobile terminal numbers of all users entering the specified area through the base station associated with the user entering the specified area to generate the first mobile terminal number list;
  • the second mobile terminal number list generation step is to identify the biological characteristics of the user, and based on the pre-established binding relationship between the biological characteristics of the user and the mobile terminal number, obtain a combination of n mobile terminal numbers with the highest similarity to the biological characteristics A list of second mobile terminal numbers, where n is a natural number greater than 1; and
  • the comparison step is to compare the first mobile terminal number list with the second mobile terminal number list, and if the intersection of the two is one mobile terminal number, then it is determined that the user of the mobile terminal number is a user with successful identity authentication, If the intersection of the two is greater than one number, it is determined that the user with the mobile terminal number with the highest biological feature similarity in the intersection is the user with successful identity authentication.
  • a predetermined encryption operation is further performed on the mobile terminal numbers of all users entering the prescribed area to generate the first mobile terminal number list,
  • the predetermined encryption operation is further performed on the N mobile terminal numbers with the highest similarity to generate the second mobile terminal number list.
  • the prescribed encryption operation is a HASH operation.
  • the biological characteristics of the user are identified, and the highest similarity to the biological characteristics is obtained based on the pre-established binding relationship between the biological characteristics of the user and the mobile terminal number.
  • m mobile terminal numbers for confusion are randomly generated, and the n mobile terminal numbers and the m mobile numbers for confusion form the second mobile terminal number list, where m is a natural number.
  • a predetermined encryption operation is further performed on the mobile terminal numbers of all users entering the prescribed area to generate the first mobile terminal number list,
  • the predetermined encryption operation is further performed on the n mobile terminal numbers and the m mobile numbers for confusion to generate the second mobile terminal number list.
  • the prescribed encryption operation is a HASH operation.
  • the step of generating the list of first mobile terminal numbers for each of the mobile terminal numbers of all users entering the prescribed area, a part of the mobile terminal numbers at a prescribed position is collected to generate The first mobile terminal number list,
  • a number at a specified position in the same part of the mobile terminal numbers is collected to generate the second mobile terminal List of numbers.
  • a predetermined encryption operation is further performed on some of the collected mobile terminal numbers at a predetermined position to generate the first mobile terminal number list
  • a predetermined encryption algorithm is further performed on the part of the collected mobile terminal numbers at the specified position to generate the second mobile terminal number list.
  • the prescribed encryption operation is a HASH operation.
  • the step of generating the list of first mobile terminal numbers for each of the mobile terminal numbers of all users entering the prescribed area, a part of the mobile terminal numbers at a prescribed position is collected to generate The first mobile terminal number list,
  • the n mobile terminal numbers with the highest similarity to the biological characteristics are obtained, and m mobile terminal numbers for confusion are randomly generated.
  • the numbers at the specified positions in the mobile terminal numbers are collected to generate the second mobile terminal number list.
  • a specified encryption algorithm is further performed on some of the collected mobile terminal numbers at a predetermined position to generate the first mobile terminal number list
  • the numbers in the same part of the collected mobile terminal numbers in the specified position are further subjected to a specified encryption algorithm to generate the second mobile terminal number list.
  • the prescribed encryption operation is a HASH operation.
  • the biological feature includes any one or a combination of the following: human face, finger vein, iris, fingerprint, palm print, and voice.
  • the prescribed areas are businesses, transportation facilities, buildings, and commercial areas.
  • a corresponding association relationship is preset between the prescribed area and the base station
  • the corresponding relationship between the prescribed area and the base station includes any one of the following:
  • One prescribed area corresponds to one base station
  • One base station corresponds to multiple prescribed areas
  • Multiple users in the prescribed area correspond to one base station.
  • the pre-established binding relationship between the user's biological characteristics and the mobile terminal number further includes bank card information.
  • the base station obtains the mobile terminal number of the user entering the coverage area of the base station in real time, and sends the mobile terminal number and the base station identification number of the user to the following base station management module;
  • the base station management module receives the user's mobile terminal number and base station identification number, and obtains the mobile terminal numbers of all users entering the specified area according to the pre-stored association relationship between the base station identification number and the specified area to generate the first mobile Terminal number list, sending the first mobile terminal number list to the following biometric identification background;
  • the biometric identification terminal is used to obtain the user's biometrics
  • the biometric identification background is used to pre-store the binding relationship between the user's biometrics and the mobile terminal number, and based on the binding relationship, obtain the n highest similarities with the biometrics of the user identified by the biometric identification terminal
  • a second mobile terminal number list composed of mobile terminal numbers, where n is a natural number greater than 1.
  • the first mobile terminal number list sent by the base station management module is received, and the first mobile The terminal number list is compared with the second mobile terminal number list. If the intersection of the two is a mobile terminal number, then the user of the mobile terminal number is judged to be a user with successful identity authentication. If the intersection of the two is greater than 1 number , It is determined that the user with the mobile terminal number with the highest biological feature similarity in the intersection is a user with successful identity authentication.
  • the biological feature database is used to pre-store the binding relationship between the user's biological feature and the mobile terminal number
  • the receiving module receives the user's biological characteristics from the outside, on the other hand, receives from the outside the first mobile terminal number list composed of the mobile terminal numbers of all users entering the specified area;
  • the biometric identification module obtains a second mobile terminal number list composed of n mobile terminal numbers with the highest similarity to the user's biometrics received by the receiving module based on the pre-stored binding relationship in the biometric database, where: n is a natural number greater than 1.
  • the first mobile terminal number list and the second mobile terminal number list are compared, and if the intersection of the two is a mobile terminal number, then the mobile terminal is judged The user with the number is the user with successful identity authentication. If the intersection of the two is greater than one number, it is determined that the user with the mobile terminal number with the highest biological feature similarity in the intersection is the user with the successful identity authentication.
  • the receiving module receives from the outside the first mobile terminal number list generated by performing a specified encryption operation on the mobile terminal numbers of all users entering the specified area,
  • the biometric identification module further performs the prescribed encryption operation on the n mobile terminal numbers with the highest similarity to generate the second mobile terminal number list.
  • the prescribed encryption operation is a HASH operation.
  • the biometric identification module further randomly generates m mobile terminal numbers for confusion, and the second mobile terminal number list is composed of the n mobile terminal numbers and the m mobile numbers for confusion.
  • the receiving module receives from the outside the first mobile terminal number list generated by performing a specified encryption operation on the mobile terminal numbers of all users entering the specified area,
  • the biometric identification module further performs the prescribed encryption operation on the n mobile terminal numbers and the m mobile numbers for confusion to generate the second mobile terminal number list.
  • the prescribed encryption operation is a HASH operation.
  • the receiving module receives from the outside the first mobile terminal number list generated by collecting a part of the mobile terminal numbers of the mobile terminal numbers for each of the mobile terminal numbers of all users entering the specified area, and
  • the biometric identification module further collects the numbers at the specified positions in the mobile terminal numbers for each of the n mobile terminal numbers with the highest similarity to generate the second mobile terminal number list.
  • the receiving module receives from the outside, for each of the mobile terminal numbers of all users entering the specified area, the first number generated by collecting a part of the mobile terminal numbers at a specified location and performing a specified encryption algorithm.
  • List of mobile terminal numbers
  • the biometric identification module further performs a specified encryption algorithm on the numbers of the same part of the collected mobile terminal numbers at the specified location to generate the second mobile terminal number list.
  • the prescribed encryption operation is a HASH operation.
  • the receiving module receives from the outside the first mobile terminal number list generated by collecting a part of the mobile terminal numbers of the mobile terminal numbers for each of the mobile terminal numbers of all users entering the specified area, and
  • the biometric authentication module obtains the n mobile terminal numbers with the highest similarity to the biological characteristics, and randomly generates m mobile terminal numbers for confusion. For the n mobile terminal numbers and the m mobile terminal numbers for confusion Each collects the numbers of the same part of the specified positions in the mobile terminal numbers to generate the second mobile terminal number list.
  • the receiving module receives from the outside, for each of the mobile terminal numbers of all users entering the specified area, the first number generated by collecting a part of the mobile terminal numbers at a specified location and performing a specified encryption algorithm.
  • List of mobile terminal numbers
  • the biometric authentication module collects the number of the same part of the mobile terminal number at the specified position for each of the n mobile terminal numbers and the m mobile numbers for confusion and performs a specified encryption algorithm to generate the second mobile Terminal number list
  • the prescribed encryption operation is a HASH operation.
  • the biological feature includes any one or a combination of the following: human face, finger vein, iris, fingerprint, palm print, and voice.
  • the prescribed areas are businesses, transportation facilities, and public facilities.
  • a corresponding association relationship is preset between the prescribed area and the base station
  • the corresponding relationship between the prescribed area and the base station includes any one of the following:
  • One prescribed area corresponds to one base station
  • One base station corresponds to multiple prescribed areas
  • Multiple users in the prescribed area correspond to one base station.
  • the base station obtains the mobile terminal number of the user entering the coverage area of the base station in real time, and sends the mobile terminal number and the base station identification number of the user to the following base station management module;
  • the base station management module receives the user's mobile terminal number and base station identification number from the base station, and obtains the mobile terminal numbers of all users entering the specified area according to the pre-stored association relationship between the base station identification number and the specified area. Generating a list of first mobile terminal numbers;
  • the biometric identification terminal is used to obtain the user's biometrics
  • the biometric identification background is used to pre-store the binding relationship between the user's biometrics and the mobile terminal number, and based on the binding relationship, obtain the n highest similarities with the biometrics of the user identified by the biometric identification terminal
  • a second mobile terminal number list composed of mobile terminal numbers, where n is a natural number greater than 1, and the second mobile terminal number list is sent to the base station management module,
  • the base station management module receives the second mobile terminal number list sent by the biometric identification background, compares the first mobile terminal number list with the second mobile terminal number list, and compares the two The intersection of the persons returns to the biometric identification background,
  • the biometric identification background judges the intersection of the two received. If the intersection of the two is a mobile terminal number, then it is judged that the user of the mobile terminal number is a user with successful identity authentication. If the intersection of the two is greater than 1. If the number is one number, it is determined that the user with the mobile terminal number with the highest biological feature similarity in the intersection is a user with successful identity authentication.
  • the first receiving module is configured to receive the mobile terminal number and the base station identification number of the user entering the coverage area of the base station sent from the base station;
  • the base station database is used for the pre-stored association relationship between the base station identification number and the specified area;
  • the first comparison processing module based on the association relationship stored in the base station database and the user's mobile terminal number and base station identification number received by the first receiving module, obtains the mobile terminal numbers of all users entering the specified area Terminal numbers to generate a list of first mobile terminal numbers;
  • the second receiving module receives a second mobile terminal number list from the outside, where the second mobile terminal number list is composed of n mobile terminal numbers with the highest similarity to the user’s biological characteristics, where n is a natural number greater than 1. ;
  • the second comparison processing module compares the first mobile terminal number list with the second mobile terminal number list, and obtains the intersection of the two.
  • the first comparison processing module further performs a prescribed encryption operation on the obtained mobile terminal numbers of all users entering the prescribed area to generate the first mobile terminal number list,
  • the second mobile terminal number list is formed by further performing the predetermined encryption operation on the n mobile terminal numbers with the highest similarity.
  • the prescribed encryption operation is a HASH operation.
  • the second mobile terminal number list is composed of n mobile terminal numbers with the highest similarity to the biological characteristics and m randomly generated mobile terminal numbers for confusion, where M is a natural number.
  • the first comparison processing module further performs a prescribed encryption operation on the mobile terminal numbers of all users entering the prescribed area to generate the first mobile terminal number list,
  • the second mobile terminal number list is a mobile terminal number list generated by further performing the predetermined encryption operation on the n mobile terminal numbers and the m mobile numbers for confusion.
  • the prescribed encryption operation is a HASH operation.
  • the first comparison processing module collects a part of the mobile terminal numbers at a prescribed position to generate the first mobile terminal number.
  • the second mobile terminal number list is a mobile terminal number list generated by collecting numbers in the same part of the mobile terminal numbers at a predetermined position for each of the n mobile terminal numbers with the highest similarity.
  • the first comparison processing module further performs a prescribed encryption operation on some of the collected mobile terminal numbers at a predetermined position to generate the first mobile terminal number list,
  • the second mobile terminal number list is a mobile terminal number list generated by further performing a predetermined encryption algorithm on the numbers at the same part of the collected mobile terminal numbers at a predetermined position.
  • the prescribed encryption operation is a HASH operation.
  • the first comparison processing module collects a part of the mobile terminal numbers at a prescribed position to generate the first mobile terminal number.
  • the second mobile terminal number list collects the numbers of the same part of the mobile terminal numbers at the specified position for each of the n mobile terminal numbers with the highest similarity to the biological characteristics and the m randomly generated mobile terminal numbers for confusion. And the generated list of mobile terminal numbers.
  • the first comparison processing module further performs a specified encryption algorithm on some of the collected mobile terminal numbers at a specified position to generate the first mobile terminal number list,
  • the second mobile terminal number list is a second mobile terminal number list that is generated by further performing a predetermined encryption algorithm on the numbers in the same part of the collected mobile terminal numbers at a predetermined position.
  • the prescribed encryption operation is a HASH operation.
  • the biological feature includes any one or a combination of the following: human face, finger vein, iris, fingerprint, palm print, and voice.
  • the prescribed areas are businesses, transportation facilities, buildings, and commercial areas.
  • a corresponding association relationship is preset between the prescribed area and the base station
  • the corresponding relationship between the prescribed area and the base station includes any one of the following:
  • One prescribed area corresponds to one base station
  • One base station corresponds to multiple prescribed areas
  • Multiple users in the prescribed area correspond to one base station.
  • the computer-readable medium of the present invention has a computer program stored thereon, and is characterized in that:
  • the computer device of the present invention includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and is characterized in that the processor implements the above-mentioned identity authentication based on biometrics when the computer program is executed. method.
  • the base station can obtain the user's mobile phone number (the base station can be a macro base station or a small base station), and the base station management module can be used to reduce the number of people.
  • the range of face recognition N As a result, users can use 1:N face recognition in an open environment, and the application scenarios of 1:N face recognition are greatly increased. At the same time, the user only needs to carry a mobile phone and can complete 1:N face recognition without additional operations.
  • Fig. 1 is a schematic diagram showing a scene of the identity authentication system and the identity authentication method based on biometrics of the present invention.
  • Fig. 2 is a schematic diagram showing the technical architecture of the biometric-based identity authentication system of the present invention.
  • FIG. 3 is a schematic diagram showing the flow of information exchange between a mobile phone, a base station, and a core network taking 4G-LTE as an example.
  • Fig. 4 is a schematic flowchart showing a new step in the present invention.
  • FIG. 5 is a schematic flow chart showing the identity authentication method based on biometrics, which is the first method of the plaintext comparison method.
  • Fig. 6 is a schematic flow chart showing the identity authentication method based on biometrics, which is the second method in the plaintext comparison method.
  • Fig. 7 is a schematic flow chart showing a method of identity authentication based on biometrics in a confusion and comparison mode.
  • FIG. 8 is a schematic flow chart showing the identity authentication method based on biometrics, which is the first method of the fuzzy comparison method.
  • FIG. 9 is a schematic flow chart showing the identity authentication method based on biometrics, which is the second method in the plaintext comparison method.
  • FIG. 10 is a schematic flowchart showing a biometric identity authentication method based on a confusion and fuzzy comparison method.
  • FIG. 11 is a schematic flowchart showing the identity authentication method based on biometrics according to the first embodiment.
  • FIG. 12 is a block diagram showing the structure of the biometrics-based identity authentication system of the first embodiment.
  • FIG. 13 is a schematic flowchart showing the identity authentication method based on biometrics according to the second embodiment.
  • FIG. 14 is a block diagram showing the structure of the biometrics-based identity authentication system of the second embodiment.
  • FIG. 15 is a schematic flow chart showing the identity authentication method based on biometrics in the third embodiment.
  • FIG. 16 is a block diagram showing the structure of the biometrics-based identity authentication system of the third embodiment.
  • Fig. 17 is a schematic flow chart showing a method for identity authentication based on biometrics in the fourth embodiment.
  • FIG. 18 is a block diagram showing the structure of a biometrics-based identity authentication system according to the fourth embodiment.
  • FIG. 19 is a schematic flow chart showing the identity authentication method based on biometrics in the fifth embodiment.
  • FIG. 20 is a block diagram showing the structure of the biometrics-based identity authentication system of the fifth embodiment.
  • FIG. 21 is a schematic flow chart showing the identity authentication method based on biometrics in the sixth embodiment.
  • Fig. 22 is a block diagram showing the structure of a biometrics-based identity authentication system according to a sixth embodiment.
  • Fig. 1 is a schematic diagram showing a scene of the identity authentication system and the identity authentication method based on biometrics of the present invention.
  • a user carries a mobile phone 1, a mobile phone 2, a mobile phone 3...
  • mobile phone corresponds to the “mobile terminal” in the claims, and the following will also take a mobile phone as an example for description
  • the biometric identification terminal collects the user's biometrics and sends them to the biometric identification
  • the base station management module can know the mobile phone number of the base station corresponding to the merchant, and through the interaction between the biometric identification background and the base station management module, the mobile phone number that is accessed from the base station is obtained to narrow the range of N.
  • biological features include, but are not limited to, any one or a combination of the following: human face, finger veins, iris, fingerprints, palm prints, and voice.
  • Fig. 2 is a schematic diagram showing the technical architecture of the biometric-based identity authentication system of the present invention.
  • the identity authentication system based on biometrics of the present invention mainly includes a base station 20, a base station management module 30, a biometric identification terminal 40, and a biometric identification background 50.
  • the base station is an improved base station used for signal coverage of indoor merchants.
  • the base station can obtain the mobile phone number of the mobile phone connected to it.
  • the base station usually uploads the information obtained to the mobile phone to the core network through the traditional communication protocol, and the obtained information of the mobile phone contains other information besides the mobile phone number, which makes it difficult for operators to obtain the mobile phone number of the base station in real time and needs to be improved.
  • Existing base station Existing base station.
  • the base station will continuously broadcast its location information.
  • the mobile phone When the mobile phone enters a new area (or is turned on), it will find that its original location information is different from the received broadcast location information, then the mobile phone information will be transmitted to the base station, and then the information will be sent to the base station.
  • the core network allows the background to re-register the location of the mobile phone.
  • the improved base station not only transmits the mobile phone related information to the core network according to the traditional communication protocol, but also sends the necessary information such as the mobile phone number to the base station management module separately.
  • FIG. 3 is a schematic diagram showing the flow of information exchange between a mobile phone, a base station, and a core network taking 4G-LTE as an example.
  • Figure 4 is a schematic diagram showing the flow of the present invention after a new step is added.
  • the base station broadcasts location information
  • the mobile phone judges whether the information has changed from the previously stored location (that is, whether it has entered a new area);
  • RA Preamble represents the random access index, and the process of 3 is to send a random access request to the base station;
  • RA Response means response to random access
  • RRCConnection Request means sending an RRC connection establishment request
  • the mobile phone information sent from the mobile phone includes (IMEI means International Mobile Equipment Identity, IMSI means International Mobile Subscriber Identity, mobile phone number, etc.) to the base station;
  • IMEI International Mobile Equipment Identity
  • IMSI International Mobile Subscriber Identity, mobile phone number, etc.
  • the base station transmits the mobile phone information and location update request information to the core network
  • step "9" as shown in Figure 4 (the base station transmits the separate mobile phone number information to the base station management module) and the base station management module It will interact with the biometric backend.
  • the biometric identification terminal 40 may be placed at the merchant checkout to collect user biometrics and prompt biometric identification results.
  • the biometric identification terminal 40 includes but is not limited to prompt devices such as a liquid crystal display, LED, etc., and is equipped with a voice reminder function to provide users with a good payment experience through a humanized service method.
  • the biometric identification background 540 includes a biometric identification module 51 and a biometric database 52.
  • the biometric database 52 stores a one-to-one correspondence between biometrics and mobile phone numbers.
  • the biometrics recognition module 51 is used to compare the collected biometrics with the biometrics in the biometric database 52 to obtain similarity. And list the mobile phone numbers of the N individuals with the highest similarity.
  • N is not limited and can be any natural number greater than 1. As an example in Table 1 below, N is taken as 10.
  • the base station management module 30 stores the corresponding relationship between the base station 20 and the merchant (of course, the corresponding relationship may also be stored in the biometric identification background 50.
  • one merchant corresponds to one base station number
  • one merchant corresponds to multiple base station numbers
  • multiple merchants correspond to one base station number.
  • Table 2 shows the business number and Correspondence of base station numbers and examples of mobile phone numbers accessed by each base station number.
  • biometrics-based identity authentication system of one aspect of the present invention may include:
  • the base station 20 obtains the mobile phone number of the mobile phone 10 of the user entering the coverage area of the base station 20 in real time, and sends the mobile phone number and the base station identification number of the user to the base station management module 50;
  • the base station management module 30 receives the user's mobile phone number and the base station identification number, and obtains the mobile phone number of the user who has entered the merchant according to the pre-stored association relationship between the base station identification number and the merchant to generate the first mobile phone number list.
  • the list of mobile phone numbers is sent to the following biometric identification background 50;
  • the biometric identification terminal 40 is used to obtain the user's biometrics
  • the biometric identification background 50 includes a biometric database 51 for pre-stored the binding relationship between the user's biometrics and the mobile phone number, and the biometrics of the user recognized by the face recognition terminal 40 are obtained based on the binding relationship.
  • a second mobile phone number list composed of N mobile phone numbers with the highest feature similarity, where N is a natural number greater than 1.
  • the first mobile phone number list sent by the base station management module 30 is received, and the first mobile phone number The list is compared with the second mobile phone number list. If the intersection of the two is a mobile phone number, then the user of the mobile phone number is judged to be a successful user. If the intersection of the two is greater than 1 number, then the intersection is judged The user with the mobile phone number with the highest biometric similarity is the user with successful identity authentication.
  • the base station management module 30 can also perform the list of the first mobile phone number and the second mobile phone number list.
  • the comparison of the mobile phone number list is as follows:
  • the identity authentication system based on biometrics may have:
  • the base station 20 obtains the mobile phone number of the user 10 entering the coverage area of the base station 20 in real time, and sends the mobile phone number and the base station identification number of the user 10 to the following base station management module 30;
  • the base station management module 30 receives the user's mobile phone number and the base station identification number from the base station 20, and obtains the mobile phone number of the user entering the merchant according to the pre-stored association relationship between the base station identification number and the merchant to generate the first mobile phone number list;
  • the biometric identification terminal 40 is used to obtain the user's biometrics
  • the biometric identification background 50 includes a biometric database 51 for pre-storing the binding relationship between the user's biometrics and mobile phone number, and a biometric database 51 for obtaining the user identified with the biometric identification terminal 40 based on the binding relationship
  • a second mobile phone number list composed of N mobile phone numbers with the highest biological feature similarity, where N is a natural number greater than 1, and the second mobile phone number list is sent to the base station management module 30,
  • the base station management module 30 receives the second mobile phone number list sent by the biometric identification background 50, compares the first mobile phone number list with the second mobile phone number list, and returns the intersection of the two to the biometric identification background 50,
  • the biometric identification background 50 judges the intersection of the two received. If the intersection of the two is a mobile phone number, the user of the mobile phone number is judged to be a user with successful identity authentication. If the intersection of the two is greater than 1 number, Then, it is determined that the user with the mobile phone number with the highest degree of similarity of the biological characteristics in the intersection is a user with successful identity authentication.
  • a 1:N scheme is adopted for biometric identification, and in order to ensure the accuracy of the identification result, the number N is controlled within a certain range through screening of mobile phone numbers.
  • the biometric-based identity authentication method of the present invention the information obtained by the interaction between the mobile terminal and the base station is used to narrow the range of N, and the recognition range is dynamically controlled in the current area (such as merchants, transportation facilities, etc.) User groups, not all registered users.
  • the "prescribed area” is taken as an example of a "merchant”
  • the mobile terminal is taken as an example of a mobile phone.
  • the biometric-based identity authentication method of the present invention as a whole includes three stages: a registration stage, a preprocessing stage, and an identification stage:
  • the user submits biometrics (such as face picture, fingerprint information, palm print information, iris information, etc.), bank card, mobile phone number, and binds them.
  • biometrics such as face picture, fingerprint information, palm print information, iris information, etc.
  • the user will enter the merchant before biometric identification.
  • the user needs to bring a mobile phone, the base station broadcasts location information, the mobile phone sends an information update request and mobile phone information to the base station, and the mobile phone number and base station number are sent to the base station management module.
  • the base station management module stores the correspondence between the base station and the merchant, and dynamically maintains a list of mobile phone numbers in the merchant, that is, dynamically provides a list of the first mobile phone numbers that access the base station.
  • the user’s biological characteristics are identified, and based on the pre-established binding relationship between the user’s biological characteristics and mobile terminal numbers, a second mobile phone number list composed of n mobile terminal numbers with the highest similarity to the biological characteristics is obtained , Where n is a natural number greater than 1, and then compare the first mobile phone number list with the second mobile phone number list to complete the biometric identification.
  • the base station management module and the biometric identification background may both have the need not to expose their own data. Therefore, the following will explain how to compare different methods to meet the needs of all parties.
  • the first mode of plain text comparison is to transfer the cell phone list from the biometric background to the base station management module.
  • the base station management module compares and returns the intersection of the cell phone number list.
  • the biometric background compares the intersection again.
  • FIG. 5 is a schematic flow chart showing the identity authentication method based on biometrics in the first mode of the plaintext comparison method.
  • step S1 the biometric identification terminal obtains the biometric characteristics of the user recognized by the biometric identification terminal. Based on the pre-established binding relationship between the user's biometrics and the mobile phone number, the biometric identification background obtains The mobile phone number list of the n mobile phone numbers with the highest similarity to the biological characteristics is sent to the base station management module, where n is a natural number greater than 1.
  • step S2 after the user enters the base station associated with the merchant, the base station management module obtains the mobile phone number list of the user who entered the merchant (this step can be performed before step S1), and then the base station management module compares and enters The intersection of the mobile phone number list in the merchant and the mobile phone number list of the n users with the highest similarity sent from the biometric identification background, and the intersection of the two is returned to the biometric identification background in step S3.
  • step S4 the biometric identification background determines whether the intersection of the two is a mobile phone number. If the intersection of the two is a mobile phone number, then go to step S5, then go to the intersection to be the final result of biometric identification, that is, the user of the mobile phone number is a user with successful identity authentication. If the intersection of the two is greater than 1 number, then In step S6, the user with the highest biometric similarity in the intersection is regarded as the final result of biometric identification, that is, the user with the mobile phone number with the highest biometric similarity in the intersection is the user with successful identity authentication.
  • the biometric backend will perform an encryption operation (such as HASH) on the mobile phone numbers of the n users with the highest similarity.
  • the base station management module will also perform the same mobile phone numbers in the list.
  • the second mode of plain text comparison is that the base station management module transmits the cell phone number list to the biometric identification background, and the biometric identification background compares the cell phone number list and the intersection of the compared cell phone number list.
  • FIG. 6 is a schematic flowchart showing the second mode of the identity authentication method based on biometrics in the plaintext comparison mode.
  • step S11 the biometric identification background initiates a request to the base station management module to obtain a list of mobile phone numbers entering the merchant.
  • step S12 the base station management module returns a list of mobile phone numbers entered into the merchant.
  • step S13 the biometric identification background obtains the biometric characteristics of the user recognized by the biometric identification terminal, and based on the pre-established binding relationship between the user's biometric characteristics and the mobile phone number, the n mobile phone numbers with the highest similarity to the biometric characteristics are obtained. Then, the biometric identification background compares whether the cell phone number list of the n cell phone numbers with the highest biometric similarity and the cell phone number list sent from the base station management module to the merchant have an intersection.
  • step S14 it is judged whether the intersection of the two is a mobile phone number, if the intersection of the two is a mobile phone number, then go to step S15 to determine that the user of the mobile phone number is a user with successful identity authentication, if the intersection of the two is greater than If there is one number, step S16 is entered, and it is determined that the user with the mobile phone number with the highest biometric similarity in the intersection is the user with successful identity authentication.
  • the base station management module can encrypt the mobile phone numbers in its list (for example, HASH, etc.) before transmitting, and the mobile phone numbers in the biometric identification list also perform the same encryption operation. ,Complete the comparison. This method can ensure that the base station management module does not expose its own data.
  • the first mode of obfuscation comparison is to add m mobile phone lists with random cell phone numbers for confusion to the base station management module by the biometric background transmission.
  • the base station management module compares and returns the intersection of the cell phone number lists.
  • the biometrics Identify the background and compare the intersection.
  • Fig. 7 is a schematic flow chart showing a method of identity authentication based on biometrics in a confusion and comparison mode.
  • the biometric identification terminal obtains the biometric characteristics of the user identified by the biometric identification terminal. Based on the pre-established binding relationship between the user's biometrics and the mobile phone number, the biometric identification background obtains The mobile phone number list of the n mobile phone numbers with the highest similarity to the biological characteristics is packaged and sent to the base station management module including n high similarity mobile phone numbers and other randomly generated m random mobile phone numbers. n is a natural number greater than 1, and m is a natural number.
  • step S22 after the user enters the coverage area of the base station associated with the merchant, the base station management module obtains the mobile phone number list of the user entering the merchant (this step can be performed before step S21), and then the base station management module compares For the mobile phone number list entering the merchant and the mobile phone number list including the mobile phone numbers of the n users with the highest similarity and m random mobile phone numbers sent from the biometric identification background, find the intersection of the two, in step S23 Return the intersection of the two to the biometric identification background.
  • step S24 the biometric identification background judges whether the intersection of the two is a mobile phone number. If the intersection of the two is a mobile phone number, go to step S25, and determine that the user of the mobile phone number is the final biometric identification result, that is, the user with successful identity authentication. If the intersection of the two is greater than 1 number, go to step S26, For the intersection, after excluding m random mobile phone numbers, the highest biometric similarity is taken as the final result, that is, the user with the highest biometric similarity is regarded as the user who is successfully authenticated.
  • the confusion comparison method is compared with the plain text comparison method. Because m random mobile phone numbers are deliberately confused with n high-similarity mobile phone numbers with biological characteristics, the base station management module cannot obtain accurate n high-similarity mobile phone numbers. The mobile phone number of a biometric feature.
  • the biometric background will perform an encryption operation (such as HASH, etc.) on the mobile phone numbers of the n users with the highest similarity and m random mobile phone numbers, and the base station management module will also list them Perform the same encryption operation on the mobile phone number in the mobile phone number list.
  • an encryption operation such as HASH, etc.
  • the base station management module will also list them Perform the same encryption operation on the mobile phone number in the mobile phone number list.
  • the first mode of the fuzzy comparison method is that the biometric identification background does not transmit a complete list of mobile phone numbers, but transmits the fixed digits in the mobile phone number to the base station management module, and the base station management module compares the received fixed digit mobile phone numbers The list and the fixed-digit mobile phone number list of the mobile phone numbers entering the merchant obtained from the base station are returned to the biometric identification background, and the biometric identification background will then compare the intersection.
  • Fig. 8 is a schematic flow chart showing the identity authentication method based on biometrics in the first mode of the fuzzy comparison method.
  • the biometric identification terminal obtains the biometric characteristics of the user recognized by the biometric identification terminal. Based on the pre-established binding relationship between the user's biometrics and the mobile phone number, the biometric identification background obtains The mobile phone number list of the n mobile phone numbers with the highest similarity to the biological characteristics is not transmitted here, but the fixed digits of the mobile phone number (such as the first three digits and the last four digits) are transmitted to the base station management module.
  • step S32 after the user enters the base station associated with the merchant, the base station management module obtains the mobile phone number list of the user who entered the merchant (this step can be performed before step S31), and the user's mobile phone number list of the user who enters the merchant is here.
  • the mobile phone number list the fixed digits of the mobile phone number (such as the first three digits and the last four digits) are also taken in the same way.
  • the base station management module compares the mobile phone number list (such as the first three digits and the last four digits) entered into the merchant with the slave bio
  • the feature recognition background includes the mobile phone numbers of the n users with the highest similarity (for example, the first three digits and the last four digits), the intersection of the two is calculated, and the intersection of the two is returned to the biometrics recognition background in step S33.
  • step S34 the biometric identification background judges whether the intersection of the two is a mobile phone number. If the intersection of the two is a mobile phone number, go to step S35, determine that the user of the mobile phone number is the final biometric identification result, that is, the user with successful identity authentication, if the intersection of the two is greater than 1 number, go to step S36, For intersection, take the highest biometric similarity as the final result, that is, the user with the mobile phone number with the highest biometric similarity as the successfully authenticated user.
  • the biometric backend will perform an encryption operation (such as HASH, etc.) on the fixed digits (such as the first three digits and the last four digits) of the phone numbers of the n users with the highest similarity.
  • the base station management module also performs the same encryption operation on the fixed digits (such as the first three digits and the last four digits) of the mobile phone numbers in its list.
  • the advantage of the fuzzy comparison method is that the base station management module and the biometric identification background cannot mutually determine the accurate mobile phone number list owned by the other party.
  • the second mode of fuzzy comparison is that the base station management module transmits the cell phone number list to the biometric identification background, and the biometric identification background compares the cell phone number list and the intersection of the compared cell phone number list.
  • FIG. 9 is a schematic flowchart showing the second mode of the identity authentication method based on biometrics in the plaintext comparison mode.
  • step S41 the biometric identification background initiates a request to the base station management module to obtain a list of mobile phone numbers entering the merchant.
  • step S42 the base station management module returns a list of mobile phone numbers entered into the merchant, where the complete mobile phone number is not returned but the fixed digits of the mobile phone number (for example, the first three digits and the last four digits).
  • step S43 the biometric identification background obtains the biometric characteristics of the user recognized by the biometric identification terminal. Based on the pre-established binding relationship between the user's biometric characteristics and the mobile phone number, the n mobile phone numbers with the highest similarity to the biometric characteristics are obtained.
  • the list of mobile phone numbers here, instead of taking the complete mobile number but the fixed digits of the mobile number (such as the first three digits and the last four digits). Then, the biometric identification background compares the mobile phone number list of the n mobile phone numbers with the highest biometric similarity (such as the first three digits and the last four digits) with the mobile phone number list (such as the previous) sent from the base station management module to enter the merchant. Whether the last four digits of the three digits) have an intersection.
  • step S44 it is judged whether the intersection of the two is a mobile phone number, if the intersection of the two is a mobile phone number, go to step S45, and judge that the user of the mobile phone number is a user with successful identity authentication. If the intersection of the two is greater than If there is one number, step S46 is entered, and it is determined that the user with the mobile phone number with the highest biometric similarity in the intersection is the user with successful identity authentication.
  • the base station management module can encrypt the fixed digits (such as the first three digits and the last four digits) of the mobile phone number in its list and then transmit it.
  • the mobile phone number in the biometric identification list The fixed number of digits (such as the first three digits and the last four digits) is also performed the same encryption operation to complete the comparison.
  • the advantage of this mode is that the base station management module and the biometric identification background cannot mutually determine the accurate mobile phone number list owned by the other party.
  • the base station management module also does not know the final biometric identification result (that is, the person who finally completes the transaction).
  • Confusion and fuzzy comparison combines two methods of confusion and fuzzy comparison.
  • FIG. 10 is a schematic flowchart showing a biometric identity authentication method based on a confusion and fuzzy comparison method.
  • the biometric identification background obtains the biometric characteristics of the user recognized by the biometric identification terminal. Based on the pre-established binding relationship between the user's biometric characteristics and the mobile phone number, the biometric identification background obtains The mobile phone number list of the fixed digits (such as the first three digits and the last four digits) of the n mobile phone numbers with the highest similarity to the biological characteristics will include the fixed digits of the n mobile phone numbers with high similarity (such as the first three digits).
  • n is a natural number greater than 1, and m is a natural number.
  • step S52 after the user enters the base station associated with the merchant, the base station management module obtains the mobile phone number list of the user who enters the merchant (this step can be performed before step S51), and only takes the fixed digits of the mobile phone number.
  • the number (such as the first three digits and the last four digits) is used as the mobile phone number list.
  • the base station management module compares the list of fixed digits (such as the first three digits and the last four digits) of the mobile phone numbers entering the merchant and sends it from the biometric identification background
  • the mobile phone number list that includes the fixed digits of the mobile phone numbers of the n users with the highest similarity (such as the first three digits and the last four digits) and the fixed digits of m random mobile phone numbers (such as the first three digits and the last four digits) , Find the intersection of the two, and return the intersection of the two to the biometric identification background in step S53.
  • step S54 the biometric identification background judges whether the intersection of the two is a mobile phone number. If the intersection of the two is a mobile phone number, go to step S55, and determine that the user of the mobile phone number is the final biometric identification result, that is, the user with successful identity authentication. If the intersection of the two is greater than 1 number, go to step S56, For the intersection, after excluding m random cell phone numbers, the final result is the highest biometric similarity, that is, the user with the cell phone number with the highest biometric similarity is regarded as a successful identity authentication user.
  • the biometric background will identify the fixed digits of the mobile phone numbers of the n users with the highest similarity (such as the first three digits and the last four digits) and the fixed digits of m random mobile phone numbers ( For example, the first three digits and the last four digits) perform encryption operations (such as HASH, etc.).
  • the base station management module also performs the same encryption operations on the fixed digits of the mobile phone number in its list (such as the first three digits and the last four digits). Compare the encrypted mobile phone number list for identity authentication.
  • the base station management module in addition to the fact that the base station management module and the biometric identification backend cannot mutually determine the accurate cell phone number list owned by the other party, the base station management module also does not know the final face recognition result (ie, the person who finally completes the transaction).
  • the biometric-based identity authentication system of the present invention collects the following information:
  • Collect user identity information including name, mobile phone number, and ID number. It is used to verify the uploaded face photos and display the face recognition results (desensitization) during registration.
  • the user's face photo After the verification is passed, it will be stored in the database and used as a comparison sample for face recognition.
  • the system will deduct the fee from the bound card through the identification result.
  • the user first collects the user's identity information, and then uploads the face photo.
  • the system verifies the user's identity information and face photo information through the public security system. After passing, it continues to collect the user's bank card information, and the system sends the bank card information to the bank.
  • the card elements are sent to the card issuing bank for verification. After passing, the collected user identity information (mobile phone number), face information and bank card information are bound.
  • a human face is taken as an example of a biometric feature.
  • various transformation methods can also be performed.
  • the human face may not be sent during registration, for example, instead of collecting biometric images of finger veins or iris or palms. Pattern.
  • finger vein biometric images when passing through the gate, place the user's finger on the finger vein collector to collect the image, and upload the image, or search and compare in the database.
  • biometrics-based identity authentication method and the biometrics-based identity authentication system of the present invention.
  • the first embodiment (the first mode of the plaintext comparison method)
  • FIG. 11 is a schematic flowchart showing a method of identity authentication based on biometrics in the first embodiment.
  • the biometric identity authentication method of the first embodiment includes the following steps: 1. After the user enters the merchant, the mobile phone sends the LAC and mobile phone number information to the base station, where LAC refers to geographic location update information , That is, when the mobile phone receives the signal broadcast by the base station and finds that the base station signal it originally received is different from the broadcast signal it has received, it will upload the information;
  • the base station (represented by the pattern between the mobile phone and the base station management module in Figure 11) sends the mobile phone number and base station number to the base station management module (equivalent to the operator);
  • the base station management module dynamically maintains a list of mobile phone numbers in the merchant according to the base station number, and the phone number is HASH encrypted;
  • the face recognition terminal collects faces
  • the face recognition terminal uploads the merchant number and face to the face recognition background
  • the face recognition background performs a 1:1 comparison of the face and the face in the face database to obtain the phone number of the n-digit face with the highest similarity, and each phone number is HASH encrypted;
  • the face recognition background will HASH encryption of n mobile phone numbers and transmit them to the base station management module;
  • the base station management module compares the HASH value of the mobile phone number in the list it maintains with the HASH value of the mobile phone number sent by the face recognition background to obtain the intersection mobile phone number;
  • intersection is 1, the only user is confirmed. If the intersection is greater than 1, the face with the highest similarity in the intersection is the final result.
  • FIG. 12 is a block diagram showing the structure of the biometrics-based identity authentication system of the first embodiment.
  • the face-based identity authentication system of the first embodiment has:
  • the base station 100 obtains the mobile phone number of the user entering the coverage area of the base station 100 in real time, and sends the mobile phone number and the base station identification number of the user to the following base station management module 101;
  • the base station management module 101 receives the user’s mobile phone number and base station identification number from the base station 100, based on the merchant number sent from the following face recognition backstage 103 and according to the pre-stored association relationship between the base station identification number and the merchant number, Obtain the mobile phone numbers of all users who have entered the merchant to generate the first mobile phone number list;
  • the face recognition terminal 102 is used to obtain the face of the user
  • the face recognition backend 103 includes: a face database 104, which is used to pre-store the binding relationship between the user’s face and mobile phone number, and a face recognition module 105, which is used to obtain the relationship with the person based on the binding relationship.
  • a second mobile phone number list composed of n mobile phone numbers with the highest facial similarity of the user recognized by the face recognition terminal, where n is a natural number greater than 1, and the second mobile phone number list and merchant number are sent to the base station for management Module 101,
  • the base station management module 101 receives the second mobile phone number list sent by the face recognition backend 103, compares the first mobile phone number list with the second mobile phone number list, and compares the two Return to the face recognition background 103.
  • the face recognition module 105 of the face recognition background 103 judges the intersection of the two received. If the intersection of the two is a mobile phone number, then the mobile phone number is judged If the intersection of the two is greater than one number, the user with the mobile phone number with the highest facial similarity in the intersection is determined to be the user with successful identity authentication.
  • the base station management module 101 includes the following sub-modules (not shown):
  • the first receiving module is configured to receive the mobile phone number and the base station identification number of the user entering the coverage area of the base station sent from the base station 100;
  • the base station database is used for the pre-stored association relationship between the base station identification number and the merchant number;
  • the second receiving module receives the second mobile phone number list and the merchant number from the outside (ie, the face recognition background 103);
  • the first comparison processing module according to the association relationship stored in the base station database, based on the user's mobile phone number and base station identification number received from the first receiving module and the merchant received from the second receiving module To obtain the mobile phone numbers of all users who have entered the merchant to generate the first mobile phone number list;
  • the second comparison processing module compares the first mobile phone number list with the second mobile phone number list, and obtains the intersection of the two.
  • the base station management module 101 can perform a HASH encryption operation on the first mobile phone number list sent from the base station 100.
  • the second mobile phone number list can also be HASH encrypted in the face recognition background 103 In this way, the base station management module 101 compares the two results after the HASH encryption operation.
  • the second embodiment (the second mode of the plaintext comparison method)
  • FIG. 13 is a schematic flowchart showing the identity authentication method based on biometrics according to the second embodiment.
  • the biometric-based identity authentication method of the second embodiment includes the following steps:
  • the mobile phone After the user enters the merchant, the mobile phone sends the location update information and mobile phone number information to the base station;
  • the base station sends the mobile phone number and base station number to the base station management module
  • the base station management module dynamically maintains a list of mobile phone numbers in the merchant according to the base station number, and the phone number is HASH encrypted;
  • the face recognition terminal collects faces
  • the face recognition terminal uploads the merchant number and face to the face recognition background
  • the face recognition background performs a 1:1 comparison of the face and the face in the face database to obtain the phone number of the n-digit face with the highest similarity, and each phone number is HASH encrypted;
  • the face recognition background requests the base station management module to obtain a list of mobile phone numbers in the merchant
  • the base station management module returns the HASH encrypted cell phone number list in the merchant to the face recognition platform
  • the face recognition background obtains the intersection of the mobile phone number list in the merchant and the mobile phone numbers of the n faces with the highest similarity. If the intersection is 1, the only user is confirmed. If the intersection is greater than 1, the face with the highest similarity in the intersection is Final Results;
  • FIG. 14 is a block diagram showing the structure of the biometrics-based identity authentication system of the second embodiment.
  • the face-based identity authentication system of the second embodiment includes:
  • the base station 200 obtains the mobile phone number of the user entering the coverage area of the base station in real time, and sends the mobile phone number and the base station identification number of the user to the following base station management module 201;
  • the base station management module 201 is used to receive the user's mobile phone number and base station identification number from the base station 200, and obtain the mobile phone numbers of all users entering the merchant according to the pre-stored association relationship between the base station identification number and the merchant to generate the first A list of mobile phone numbers, and sending the first list of mobile phone numbers to the following face recognition background 202;
  • the face recognition terminal 202 is used to obtain the face of the user
  • the face recognition backend 203 includes: a face database 204, which is used to pre-store the binding relationship between the user’s face and mobile phone number, and a face recognition module 205, which is used to obtain the binding relationship with the person based on the binding relationship.
  • a second mobile phone number list composed of n mobile phone numbers with the highest facial similarity of the user recognized by the face recognition terminal, where n is a natural number greater than 1.
  • the first mobile phone number list sent by the base station management module 201 is received.
  • the mobile phone number list is compared with the second mobile phone number list. If the intersection of the two is one mobile phone number, it is determined that the user of the mobile phone number is a user with successful identity authentication. If the intersection of persons is greater than one number, it is determined that the user with the mobile phone number with the highest facial similarity in the intersection is the user with successful identity authentication.
  • the base station management module 101 can perform a HASH encryption operation on the first mobile phone number list sent from the base station 100.
  • the second mobile phone number list can also be HASH encrypted in the face recognition background 103 Calculate and compare the two after HASH encryption operation.
  • the third embodiment (the first mode of the confusion comparison method)
  • FIG. 15 is a schematic flow chart showing the identity authentication method based on biometrics in the third embodiment.
  • the biometric-based identity authentication method of the third embodiment includes the following steps:
  • the mobile phone After the user enters the merchant, the mobile phone sends the location update information and mobile phone number information to the base station;
  • the base station sends the mobile phone number and base station number to the base station management module
  • the base station management module dynamically maintains a list of mobile phone numbers in the merchant according to the base station number, and the phone number is HASH encrypted;
  • the face recognition terminal collects faces
  • the face recognition terminal uploads the merchant number and face to the face recognition background
  • the face recognition background performs a 1:1 comparison of the face and the face in the face database to obtain the phone number of the n-digit face with the highest similarity, and randomly generates m confusion phone numbers to form a list.
  • Each mobile phone number is HASH encrypted, where m is a natural number;
  • the face recognition background transmits the HASH-encrypted n-digit mobile phone number and m mobile phone numbers for confusion to the base station management module;
  • the base station management module compares the mobile phone number list maintained by it with the mobile phone number list sent by the face recognition background to obtain the intersection;
  • intersection is 1, the only user is confirmed. If the intersection is greater than 1, the face with the highest similarity in the intersection is the final result;
  • FIG. 16 is a block diagram showing the structure of the biometrics-based identity authentication system of the third embodiment.
  • the biometrics-based identity authentication system of the third embodiment has:
  • the base station 300 obtains the mobile phone number of the user entering the coverage area of the base station in real time, and sends the mobile phone number and the base station identification number of the user to the following base station management module 301;
  • the base station management module 301 receives the user's mobile phone number and base station identification number from the base station 300, and obtains the mobile phone numbers of all users entering the merchant according to the pre-stored association relationship between the base station identification number and the merchant's merchant number to generate List of first mobile phone numbers;
  • the face recognition terminal 302 is used to obtain the face of the user
  • the face recognition backend 303 includes: a face database 304, used to pre-store the binding relationship between the user’s face and mobile phone number, and a face recognition module 305, used to obtain a relationship with the person based on the binding relationship.
  • a second mobile phone number list composed of n mobile phone numbers with the highest facial similarity of the user recognized by the face recognition terminal, where n is a natural number greater than 1, and the second mobile phone number list further contains m randomly generated confusion Mobile phone number composition, where m is a natural number, and the second mobile phone number list is sent to the base station management module 301.
  • the base station management module 301 receives the second mobile phone number list sent by the face recognition background 303, compares the first mobile phone number list with the second mobile phone number list, and returns the intersection of the two to the face recognition background 303.
  • the face recognition module 305 in the face recognition backstage 303 first excludes m mobile phone numbers for confusion, and then makes a judgment. If the intersection of the two is 1 mobile phone number, then the mobile phone number is judged If the intersection of the two is greater than one number, the user with the mobile phone number with the highest facial similarity in the intersection is determined to be the user with successful identity authentication.
  • the base station management module 301 can perform the HASH encryption operation on the first mobile phone number list.
  • the face recognition backend 303 also performs the HASH encryption operation on the second mobile phone number list, so that the base station management The module 301 compares the two results after the HASH encryption operation.
  • the fourth embodiment (the first mode of the fuzzy comparison method)
  • Fig. 17 is a schematic flow chart showing a method for identity authentication based on biometrics in the fourth embodiment.
  • the HASH encryption method is adopted, and the first 3 digits and the last 4 digits of the mobile phone number are used for obfuscation.
  • the biometric-based identity authentication method of the fourth embodiment includes the following steps:
  • the mobile phone After the user enters the merchant, the mobile phone sends the location update information and mobile phone number information to the base station;
  • the base station sends the mobile phone number and base station number to the base station management module
  • the base station management module dynamically maintains a list of mobile phone numbers in the merchant based on the base station number, and encrypts the first three and last four digits of the phone number HASH;
  • the face recognition terminal collects faces
  • the face recognition terminal uploads the merchant number and face to the face recognition background
  • the face recognition background performs a 1:1 comparison of the face and the face in the face database to obtain the mobile phone numbers of the n faces with the highest similarity, and do the first three and the last four digits of each mobile phone number.
  • HASH encryption, n is a natural number
  • the face recognition background will transmit the HASH encrypted mobile phone number (first three and last four digits) to the base station management module;
  • the base station management module compares the list of mobile phone numbers maintained by it with the list of mobile phone numbers sent by the face recognition background to obtain the intersection of the two;
  • intersection is 1, the only user is confirmed. If the intersection is greater than 1, the face with the highest similarity in the intersection is the final result;
  • FIG. 18 is a block diagram showing the structure of a biometrics-based identity authentication system according to the fourth embodiment.
  • the biometrics-based identity authentication system of the fourth embodiment has:
  • the base station 400 obtains the mobile phone number of the user entering the coverage area of the base station in real time, and sends the mobile phone number and the base station identification number of the user to the following base station management module 401;
  • the base station management module 401 receives the user's mobile phone number and the base station identification number from the base station 300, and obtains the mobile phone numbers of all users who have entered the merchant according to the pre-stored association relationship between the base station identification number and the merchant number and obtains the mobile phone number To generate the first mobile phone number list;
  • the face recognition terminal 402 is used to obtain the face of the user
  • the face recognition backend 403 includes: a face database 404, which is used to pre-store the binding relationship between the user’s face and mobile phone number, and a face recognition module 405, which is used to obtain a connection with the person based on the binding relationship.
  • the face recognition terminal recognizes the n mobile phone numbers with the highest facial similarity of the user, and takes the first three or four last digits of these mobile phone numbers to form a second mobile phone number list, where n is a natural number greater than 1, and the second The mobile phone number list and the merchant number are sent to the base station management module 401.
  • the base station management module 401 receives the second mobile phone number list sent by the face recognition background 403, compares the first mobile phone number list with the second mobile phone number list, and returns the intersection of the two to the face recognition background 403.
  • the face recognition module 405 in the face recognition background 403 judges the intersection of the two received. If the intersection of the two is a mobile phone number, then it is judged that the user of the mobile phone number is a user with successful identity authentication. If the intersection is greater than one number, it is determined that the user with the mobile phone number with the highest facial similarity in the intersection is the user with successful identity authentication.
  • the base station management module 401 includes (not shown):
  • the first receiving module is configured to receive the mobile phone number and the base station identification number of the user entering the coverage area of the base station sent from the base station 400;
  • the base station database is used for the pre-stored association relationship between the base station identification number and the merchant number of the merchant;
  • the first comparison processing module based on the association relationship stored in the base station database and the user's mobile phone number and base station identification number received by the first receiving module, obtains the mobile phone numbers of all users entering the merchant and Take the first three or four last digits of the mobile phone number to generate the first mobile phone number list;
  • the second receiving module receives a second mobile phone number list from the outside (ie, face recognition backend 403), where the second mobile phone number list consists of the n mobile phone numbers with the highest similarity to the user’s biological characteristics, and the mobile phone number The first three and four last digits are composed, where n is a natural number greater than 1;
  • the second comparison processing module compares the first mobile phone number list with the second mobile phone number list, and obtains the intersection of the two.
  • the base station management module 401 can perform the HASH encryption operation on the first mobile phone number list.
  • the face recognition backend 403 also performs the HASH encryption operation on the second mobile phone number list, so that the base station management module 401 compares the two results after the HASH encryption operation.
  • FIG. 19 is a schematic flow chart showing the identity authentication method based on biometrics in the fifth embodiment.
  • the HASH encryption method is adopted, and the first three and the last four digits of the mobile phone number are taken for obfuscation.
  • the biometrics-based identity authentication method of the second embodiment includes the following steps:
  • the mobile phone After the user enters the merchant, the mobile phone sends the location update information and mobile phone number information to the base station;
  • the base station sends the mobile phone number and base station number to the base station management module
  • the base station management module dynamically maintains a list of mobile phone numbers in the merchant based on the base station number, and encrypts the first three and last four digits of the mobile phone number;
  • the face recognition terminal collects faces
  • the face recognition terminal uploads the merchant number and face to the face recognition background
  • the face recognition background performs a 1:1 comparison on the face and the face in the face database, and obtains the phone number of the n-digit face with the highest similarity.
  • the first three and the last four digits of each phone number are HASH encrypted ;
  • the face recognition background requests the base station management module to obtain a list of mobile phone numbers in the merchant
  • the base station management module returns the HASH-encrypted list of the first three and the last four digits of the mobile phone number in the merchant to the face recognition platform;
  • the face recognition background obtains the intersection of the mobile phone number list in the merchant and the mobile phone numbers of the n faces with the highest similarity. If the intersection is 1, the only user is confirmed. If the intersection is greater than 1, the face with the highest similarity in the intersection is Final Results.
  • FIG. 20 is a block diagram showing the structure of the biometrics-based identity authentication system of the fifth embodiment.
  • the face-based identity authentication system of the fifth embodiment includes:
  • the base station 600 obtains the mobile phone number of the user entering the coverage area of the base station in real time, and sends the mobile phone number and the base station identification number of the user to the following base station management module 601;
  • the base station management module 601 is used to receive the user's mobile phone number and base station identification number from the base station 600, and obtain the mobile phone numbers of all users who have entered the merchant according to the pre-stored association relationship between the base station identification number and the merchant's merchant number And take the first three and the last four digits of the mobile phone number for fuzzy processing to generate a first mobile phone number list, and send the first mobile phone number list to the following face recognition background 602;
  • the face recognition terminal 602 is used to obtain the face of the user
  • the face recognition backend 603 includes: a face database 604, which is used to pre-store the binding relationship between the user’s face and the mobile phone number, and a face recognition module 505, which is used to obtain the relationship with the person based on the binding relationship.
  • the face recognition terminal recognizes the n mobile phone numbers with the highest facial similarity of the user and takes the first three and the last four digits of the mobile phone number to form a second mobile phone number list after blurring, where n is a natural number greater than 1.
  • intersection of the two is one mobile phone number, then determine the A user with a mobile phone number is a user with successful identity authentication. If the intersection of the two is greater than one number, it is determined that the user with the mobile phone number with the highest facial similarity in the intersection is a user with a successful identity authentication.
  • the base station management module 501 can perform the HASH encryption operation on the first mobile phone number list.
  • the face recognition background 503 perform the HASH encryption operation on the second mobile phone number list and compare the HASH encryption operation. Both.
  • FIG. 21 is a schematic flow chart showing the identity authentication method based on biometrics in the sixth embodiment.
  • the HASH encryption method is adopted, and the first three and the last four digits of the mobile phone number are taken for obfuscation.
  • the biometric-based identity authentication method of the sixth embodiment includes the following steps:
  • the mobile phone After the user enters the merchant, the mobile phone sends the location update information and mobile phone number information to the base station;
  • the base station sends the mobile phone number and base station number to the base station management module
  • the base station management module dynamically maintains a list of mobile phone numbers in the merchant based on the base station number, and the first three and the last four digits of the mobile phone number are HASH encrypted;
  • the face recognition terminal collects faces
  • the face recognition terminal uploads the merchant number and face to the face recognition background
  • the face recognition background performs a 1:1 comparison of the face and the face in the face database to obtain the phone number of the n-digit face with the highest similarity, and randomly generates m confusion phone numbers to form a list.
  • the first three and last four digits of each mobile phone number are HASH encrypted, and m is a natural number;
  • the face recognition background will transmit the m mobile phone numbers and n mobile phone numbers that have been HASH encrypted to the base station management module;
  • the base station management module compares the list of mobile phone numbers maintained by it with the list of mobile phone numbers sent from the face recognition background to obtain the HASH value of the intersection mobile phone number;
  • intersection is 1, the only user is confirmed. If the intersection is greater than 1, m mobile phone numbers for confusion are excluded first, and then the face with the highest similarity in the intersection is the final result;
  • Fig. 22 is a block diagram showing the structure of a biometrics-based identity authentication system according to a sixth embodiment.
  • the face-based identity authentication system of the fifth embodiment includes:
  • the base station 600 obtains the mobile phone number of the user entering the coverage area of the base station in real time, and sends the mobile phone number and the base station identification number of the user to the following base station management module 601;
  • the base station management module 601 receives the user's mobile phone number and the base station identification number from the base station 300, and obtains the mobile phone numbers of all users entering the merchant based on the pre-stored association relationship between the base station identification number and the merchant number and obtains the mobile phone number To generate the first mobile phone number list;
  • the face recognition terminal 602 is used to obtain the face of the user
  • the face recognition backend 603 includes: a face database 604, which is used to pre-store the binding relationship between the user’s face and mobile phone number, and a face recognition module 605, which is used to obtain the binding relationship with the person
  • the face recognition terminal recognizes the n mobile phone numbers with the highest facial similarity of the user and takes the first three or four last digits of these mobile phone numbers to form the second mobile phone number list, where n is a natural number greater than 1, and m confusions are added
  • the mobile phone numbers form a second mobile phone number list, and the second mobile phone number list and the merchant number are sent to the base station management module 601, where m is a natural number.
  • the base station management module 601 receives the merchant number sent by the face recognition background 603, compares the first mobile phone number list with the second mobile phone number list, and returns the intersection of the two to the face recognition background 603.
  • the face recognition module 605 in the face recognition backstage 603 For the face recognition module 605 in the face recognition backstage 603, for the received intersection of the two, it first excludes the m confusion collection numbers, and then judges. If the intersection of the two is 1 mobile phone number, then judge the mobile phone number If the intersection of the two is greater than one number, the user with the mobile phone number with the highest facial similarity in the intersection is determined to be the user with successful identity authentication.
  • the base station management module 601 includes (not shown):
  • the first receiving module is configured to receive the mobile phone numbers and base station identification numbers of users who enter the coverage area of the base station from the base station 600;
  • the base station database is used for the pre-stored association relationship between the base station identification number and the merchant number of the merchant;
  • the first comparison processing module based on the association relationship stored in the base station database and the user's mobile phone number and base station identification number received by the first receiving module, obtains the mobile phone numbers of all users entering the merchant and Take the first three or four last digits of the mobile phone number to generate the first mobile phone number list;
  • the second receiving module receives a second mobile phone number list from the outside (ie, face recognition backend 603), where the second mobile phone number list is composed of n mobile phone numbers with the highest similarity to the user’s biological characteristics and m confusions.
  • the mobile phone number is composed of the first three or four last digits of the mobile phone number, where n is a natural number greater than 1;
  • the second comparison processing module compares the first mobile phone number list with the second mobile phone number list, and obtains the intersection of the two.
  • the base station management module 601 can perform the HASH encryption operation on the first mobile phone number list.
  • the face recognition background 603 also performs the HASH encryption operation on the second mobile phone number list, so that the base station management module 601 compares the two results after the HASH encryption operation.
  • the base station can obtain the user's mobile phone number (the base station can be a macro base station or a small base station), and the base station management module can be used to reduce the number of people.
  • the range of face recognition N As a result, users can use 1:N face recognition in an open environment, and the application scenarios of 1:N face recognition are greatly increased. At the same time, the user only needs to carry a mobile phone and can complete 1:N face recognition without additional operations.
  • the present invention also provides a computer readable medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the above-mentioned biometric-based identity authentication method is realized.
  • the present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the processor implements the above-mentioned biometric-based feature when the computer program is executed by the processor.
  • the identity authentication method includes
  • these computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment to form a machine, so that the instructions executed by the processor of the computer or other programmable data processing equipment are created for implementation.
  • These flowcharts and/or blocks and/or one or more flow block diagrams specify the function/operation components.
  • these computer program instructions can also be loaded on a computer or other programmable data processor so that a series of operation steps are executed on the computer or other programmable processor, so as to form a computer-implemented process, so that the computer or other
  • These instructions executed on the programmable data processor provide steps for implementing the functions or operations specified in one or more blocks of this flowchart and/or block diagram. It should also be noted that in some alternative implementations, the functions/operations shown in the blocks may occur out of the order shown in the flowcharts.

Abstract

本发明的涉及基于生物特征的身份认证方法及其系统。该方法包括：通过用户进入到规定区域所相关联的基站获得进入到该规定区域的所有的用户的移动终端号码以生成第一移动终端号码列表；识别用户的生物特征，基于用户的生物特征与移动终端号码之间预先建立的绑定关系，获得与生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表；以及将第一移动终端号码列表与第二移动终端号码列表进行比较，如果两者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中生物特征相似度最高的移动终端号码的用户为身份认证成功用户。根据本发明，能够达到缩小人脸识别N的范围，同时用户只需要携带手机，不需要额外的操作就可以完成1：N人脸识别。

Description

基于生物特征的身份认证方法及其身份认证系统 技术领域
本发明涉及计算机技术，具体地涉及基于生物特征的身份认证方法以及基于生物特征的身份认证系统。
背景技术
目前，人脸识别技术飞速发展，技术成熟度已经基本满足金融应用对识别准确率、识别效率的要求，多用于支付、公安场景中。例如iPhone X推出Face ID功能、支付宝试点刷脸支付、农行推出刷脸取款等。人脸识别技术正成为发展最为迅速、应用前景最为广阔的生物识别技术之一。
人脸识别在技术方案上，根据识别范围数量的不同，被业界分为普遍认为有1:1与1：N两种。1:1是指在识别过程中，已知样本图片中人脸信息，将被识别图片与已知样本人脸照片进行比对，判断是否是照片中同一人脸。1：N是指在识别过程中，已有人脸样本库，库中有N个样本照片，被识别的人脸照片与库中样本进行比对，识别出人脸图片属于库中的某一个样本。
当前，在1:N应用的时候，受限于目前技术的局限性，当库中的人脸数据个数N较大时，识别结果的准确率出现显著下降。即有可能错误的脸的相似度会高于正确的脸。因此在非封闭大流量场景1:N的应用难度很高。
另外，5G技术也是近两年较为火热的技术，5G时代基站部署将发生变化将是室外“宏基站”打底加室内多“小基站”补充的组合。小基站具有信号覆盖区域有限、易部署、自优化和低成本等特点，未来将是室内场景的支柱。同时运营商可获知接入小基站的用户手机号，利用这个特性，与运营商合作，可以形成一种基于5G基站的人脸识别方法。
作为现有技术，目前的1：N人脸识别主要有三种模式：
第一种是封闭式的环境下的人脸识别，比如园区，校园这种区域范围小，N可控有固定上限的环境。
第二种是通过辅助的手法去缩小N，比如支付宝的人脸识别需要用户输入手机号后4位去缩小N。
第三种是通过5G基站获取用户手机号码和对应的位置信息，然后根据用户常用的历史位置信息，将用户的人脸特征从云端的数据库中发送到离用户常用的历史位置最近的边缘节点上进行保存。识别时，比对在边缘节点保存的人脸数据 库进行识别，降低N的范围。
第四种是用户在注册时，注册人脸和手机蓝牙mac地址，在识别时，打开手机蓝牙功能，通过商户接入的mac地址来降低N的范围。
但是，上述现有技术存在以下的缺点：
(1)第一种模式局限了人脸识别的使用范围，在开放式的一些场景比如商超、餐厅等无法去做到人脸识别。
(2)第二种模式用户还需去进行额外的操作去降低N的方位，降低了用户使用人脸识别的用户体验。
(3)上述第三种模式所述方法需要额外构造边缘设备节点，并且通过历史位置记录人脸的方法准确度较低，容易出现识别不出的情况。
(4)第四种模式在识别时，需要用户打开手机蓝牙功能，蓝牙功能不是一个用户常用功能，相当于需要用户去进行额外的打开操作，用户体验较差。
发明内容
鉴于上述问题，本发明旨在提出一种能够在开放式环境下准确实现身份认证的基于生物特征的身份认证方法以及基于生物特征的身份认证系统。
本发明的基于生物特征的身份认证方法，该方法是基于用户的生物特征以及用户所携带的移动终端进行身份认证的方法，其特征在于，包括下述步骤：
第一移动终端号码列表生成步骤，通过用户进入到规定区域所相关联的基站获得进入到该规定区域的所有的用户的移动终端号码以生成第一移动终端号码列表；
第二移动终端号码列表生成步骤，识别用户的生物特征，基于用户的生物特征与移动终端号码之间预先建立的绑定关系，获得与所述生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表，其中，n为大于1的自然数；以及
比较步骤，将所述第一移动终端号码列表与所述第二移动终端号码列表进行比较，如果两者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的移动终端号码的用户为身份认证成功用户。
可选地，在所述第一移动终端号码列表生成步骤中，对于所述进入到该规定区域的所有的用户的移动终端号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
在所述第二移动终端号码列表生成步骤中，对于所述相似度最高的N个移 动终端号码进一步进行所述规定的加密运算以生成所述第二移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，在所述第二移动终端号码列表生成步骤中，识别用户的生物特征，基于用户的生物特征与移动终端号码之间预先建立的绑定关系，获得与所述生物特征相似度最高的n个移动终端号码，同时随机生成m个混淆用移动终端号码，所述n个移动终端号码和所述m个混淆用移动号码组成所述第二移动终端号码列表，其中m为自然数。
可选地，在所述第一移动终端号码列表生成步骤中，对于所述进入到该规定区域的所有的用户的移动终端号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
在所述第二移动终端号码列表生成步骤中，对于所述n个移动终端号码和所述m个混淆用移动号码进一步进行所述规定的加密运算生成所述第二移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，在所述第一移动终端号码列表生成步骤中，对于所述进入到该规定区域的所有的用户的移动终端号码的每一个，采集移动终端号码中的部分规定位置的号码以生成所述第一移动终端号码列表，
在所述第二移动终端号码列表生成步骤中，对于所述相似度最高的n个移动终端号码的每一个，采集移动终端号码中的相同的部分规定位置的号码以生成所述第二移动终端号码列表。
可选地，在所述第一移动终端号码列表生成步骤中，对于所述采集的移动终端号码中的部分规定位置的号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
在所述第二移动终端号码列表生成步骤中，对于所述采集的移动终端号码中的所述部分规定位置的号码进一步进行规定的加密算法以生成所述第二移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，在所述第一移动终端号码列表生成步骤中，对于所述进入到该规定区域的所有的用户的移动终端号码的每一个，采集移动终端号码中的部分规定位置的号码以生成所述第一移动终端号码列表，
在所述第二移动终端号码列表生成步骤中，获得与所述生物特征相似度最高的n个移动终端号码，同时随机生成m个混淆用移动终端号码，对于所述n个 移动终端号码和所述m个混淆用移动号码的每一个，采集移动终端号码中的所述部分规定位置的号码以生成所述第二移动终端号码列表。
可选地，在所述第一移动终端号码列表生成步骤中，对于所述采集的移动终端号码中的部分规定位置的号码进一步进行规定的加密算法以生成所述第一移动终端号码列表，
在所述第二移动终端号码列表生成步骤中，所述采集的移动终端号码中的相同的部分规定位置的号码进一步进行规定的加密算法以生成所述第二移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，所述生物特征包括下述的任意一种或者多种的组合：人脸、指静脉、虹膜、指纹、掌纹以及声音。
可选地，所述规定区域是商户、交通设施、大楼、商业区。
可选地，所述规定区域与所述基站之间预先设置对应关联关系，
所述规定区域与所述基站之间的所述对应关联关系包括下述任意一种：
一个述规定区域与一个基站对应；
一个基站与多个规定区域对应；以及
多个述规定区域户与一个基站对应。
可选地，所述用户的生物特征与移动终端号码之间预先建立的绑定关系中进一步包含银行卡信息。
本发明的基于生物特征的身份认证系统，其特征在于，具备：
基站，实时获取进入到该基站覆盖区域的用户的移动终端号码，将用户的移动终端号码和基站标识号发送给下述的基站管理模块；
基站管理模块，接收用户的移动终端号码和基站标识号，根据预先存储的基站标识号与规定区域之间的关联关系，获得进入到所述规定区域的所有用户的移动终端号码以生成第一移动终端号码列表，将所述第一移动终端号码列表发送至下述的生物特征识别后台；
生物特征识别终端，用于获取用户的生物特征；
生物特征识别后台，用于预先存储用户的生物特征与移动终端号码之间的绑定关系，基于所述绑定关系获得与所述生物特征识别终端识别的用户的生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表，其中，n为大于1的自然数，另一方面，接收所述基站管理模块发送来的所述第一移动终端号码列表，并将所述第一移动终端号码列表与所述第二移动终端号码列表进行比 较，如果两者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的移动终端号码的用户为身份认证成功用户。
本发明的生物特征识别后台，其特征在于，具备：
生物特征数据库，用于预先存储用户的生物特征与移动终端号码之间的绑定关系；
接收模块，从外部接收用户的生物特征，另一方面，从外部接收进入到规定区域的所有用户的移动终端号码构成的第一移动终端号码列表；
生物特征识别模块，基于所述生物特征数据库中预先存储的绑定关系获得与所述接收模块接收的用户的生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表，其中，n为大于1的自然数，另一方面，并将所述第一移动终端号码列表与所述第二移动终端号码列表进行比较，如果两者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的移动终端号码的用户为身份认证成功用户。
可选地，所述接收模块从外部接收对进入到规定区域的所有用户的移动终端号码进行规定的加密运算后生成的第一移动终端号码列表，
所述生物特征识别模块对于所述相似度最高的n个移动终端号码进一步进行所述规定的加密运算以生成所述第二移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，所述生物特征识别模块进一步随机生成m个混淆用移动终端号码，由所述n个移动终端号码和所述m个混淆用移动号码组成所述第二移动终端号码列表。
可选地，所述接收模块从外部接收对进入到规定区域的所有用户的移动终端号码进行规定的加密运算后生成的第一移动终端号码列表，
所述生物特征识别模块进一步对于所述n个移动终端号码和所述m个混淆用移动号码进一步进行所述规定的加密运算生成所述第二移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，所述接收模块从外部接收对于进入到规定区域的所有用户的移动终端号码的每一个采集移动终端号码中的部分规定位置的号码而生成的所述第一移动终端号码列表，
所述生物特征识别模块进一步对于所述相似度最高的n个移动终端号码的 每一个，采集移动终端号码中的所述部分规定位置的号码以生成所述第二移动终端号码列表。
可选地，所述接收模块从外部接收对于进入到规定区域的所有用户的移动终端号码的每一个采集移动终端号码中的部分规定位置的号码并进行规定的加密算法而生成的所述第一移动终端号码列表，
所述生物特征识别模块进一步对于所述采集的移动终端号码中的相同的部分规定位置的号码进一步进行规定的加密算法以生成所述第二移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，所述接收模块从外部接收对于进入到规定区域的所有用户的移动终端号码的每一个采集移动终端号码中的部分规定位置的号码而生成的所述第一移动终端号码列表，
所述生物认证模块获得与所述生物特征相似度最高的n个移动终端号码，同时随机生成m个混淆用移动终端号码，对于所述n个移动终端号码和所述m个混淆用移动号码的每一个采集移动终端号码中的相同的部分规定位置的号码以生成所述第二移动终端号码列表。
可选地，所述接收模块从外部接收对于进入到规定区域的所有用户的移动终端号码的每一个采集移动终端号码中的部分规定位置的号码并进行规定的加密算法而生成的所述第一移动终端号码列表，
所述生物认证模块对于所述n个移动终端号码和所述m个混淆用移动号码的每一个采集移动终端号码中的相同的部分规定位置的号码进行规定的加密算法以生成所述第二移动终端号码列表
可选地，所述规定的加密运算为HASH运算。
可选地，所述生物特征包括下述的任意一种或者多种的组合：人脸、指静脉、虹膜、指纹、掌纹以及声音。
可选地，所述规定区域是商户、交通设施以及公共设施。
可选地，所述规定区域与所述基站之间预先设置对应关联关系，
所述规定区域与所述基站之间的所述对应关联关系包括下述任意一种：
一个述规定区域与一个基站对应；
一个基站与多个规定区域对应；以及
多个述规定区域户与一个基站对应。
本发明的基于生物特征的身份认证系统，其特征在于，具备：
基站，实时获取进入到该基站覆盖区域的用户的移动终端号码，将用户的移动终端号码和基站标识号发送给下述的基站管理模块；
基站管理模块，从所述基站接收用户的移动终端号码和基站标识号，根据预先存储的基站标识号与规定区域之间的关联关系，获得进入到所述规定区域的所有用户的移动终端号码以生成第一移动终端号码列表；
生物特征识别终端，用于获取用户的生物特征；
生物特征识别后台，用于预先存储用户的生物特征与移动终端号码之间的绑定关系，基于所述绑定关系获得与所述生物特征识别终端识别的用户的生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表，其中，n为大于1的自然数，并将所述第二移动终端号码列表发送到所述基站管理模块，
其中，所述基站管理模块接收所述生物特征识别后台发送来的所述第二移动终端号码列表，并将所述第一移动终端号码列表与所述第二移动终端号码列表进行比较并且将两者的交集返回到所述生物特征识别后台，
所述生物特征识别后台对于接收到的两者的交集进行判断，如果两者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的移动终端号码的用户为身份认证成功用户。
本发明的基站管理模块，其特征在于，具备：
第一接收模块，用于接收从基站发送来的进入到该基站覆盖区域的用户的移动终端号码和基站标识号；
基站数据库，用于预先存储的基站标识号与规定区域之间的关联关系；
第一比对处理模块，基于所述基站数据库存储的所述关联关系和所述第一接收模块接收到的用户的移动终端号码和基站标识号，获得进入到所述规定区域的所有用户的移动终端号码以生成第一移动终端号码列表；
第二接收模块，从外部接收第二移动终端号码列表，其中，所述第二移动终端号码列表由与用户的生物特征相似度最高的n个移动终端号码组成，其中，n为大于1的自然数；
第二比对处理模块，将所述第一移动终端号码列表与所述第二移动终端号码列表进行比较，并获得两者的交集。
可选地，所述第一比对处理模块对于获得的所述进入到该规定区域的所有的用户的移动终端号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
所述第二移动终端号码列表是由对于所述相似度最高的n个移动终端号码进一步进行所述规定的加密运算而构成的。
可选地，所述规定的加密运算为HASH运算。
可选地，所述第二移动终端号码列表是由与所述生物特征相似度最高的n个移动终端号码和被随机生成m个混淆用移动终端号码构成，其中M为自然数。
可选地，所述第一比对处理模块对于所述进入到该规定区域的所有的用户的移动终端号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
所述第二移动终端号码列表是由对于所述n个移动终端号码和所述m个混淆用移动号码进一步进行所述规定的加密运算后而生成的移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，所述第一比对处理模块对于所述进入到该规定区域的所有的用户的移动终端号码的每一个，采集移动终端号码中的部分规定位置的号码以生成所述第一移动终端号码列表，
所述第二移动终端号码列表是对于所述相似度最高的n个移动终端号码的每一个，采集移动终端号码中的相同的部分规定位置的号码而生成的移动终端号码列表。
可选地，所述第一比对处理模块对于所述采集的移动终端号码中的部分规定位置的号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
所述第二移动终端号码列表是对于所述采集的移动终端号码中的相同的部分规定位置的号码进一步进行规定的加密算法而生成的移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，所述第一比对处理模块对于所述进入到该规定区域的所有的用户的移动终端号码的每一个，采集移动终端号码中的部分规定位置的号码以生成所述第一移动终端号码列表，
所述第二移动终端号码列表对于与所述生物特征相似度最高的n个移动终端号码以及被随机生成m个混淆用移动终端号码的每一个采集移动终端号码中的相同的部分规定位置的号码而生成的移动终端号码列表。
可选地，所述第一比对处理模块对于所述采集的移动终端号码中的部分规定位置的号码进一步进行规定的加密算法而生成所述第一移动终端号码列表，
所述第二移动终端号码列表是对于所述采集的移动终端号码中的相同的部分规定位置的号码进一步进行规定的加密算法而生成的第二移动终端号码列表。
可选地，所述规定的加密运算为HASH运算。
可选地，所述生物特征包括下述的任意一种或者多种的组合：人脸、指静脉、虹膜、指纹、掌纹以及声音。
可选地，所述规定区域是商户、交通设施、大楼、商业区。
可选地，所述规定区域与所述基站之间预先设置对应关联关系，
所述规定区域与所述基站之间的所述对应关联关系包括下述任意一种：
一个述规定区域与一个基站对应；
一个基站与多个规定区域对应；以及
多个述规定区域户与一个基站对应。
本发明的的计算机可读介质，其上存储有计算机程序，其特征在于，
该计算机程序被处理器执行时实现上述的基于生物特征的身份认证方法。
本发明的计算机设备，包括存储器、处理器以及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现上述的基于生物特征的身份认证方法。
如上所述，根据本发明的基于生物特征的身份认证方法以及基于生物特征的身份认证系统，基站可以获取用户手机号(基站可以是宏基站也可是小基站)，可利用基站管理模块达到缩小人脸识别N的范围。由此，用户可以在开放式的环境里使用1：N人脸识别，1：N人脸识别的应用场景大大增多。同时用户只需要携带手机，不需要额外的操作就可以完成1：N人脸识别。
附图说明
图1是表示本发明的基于生物特征的身份认证系统以及身份认证方法的场景示意图。
图2是表示本发明的基于生物特征的身份认证系统技术构架的示意图。
图3是表示以4G-LTE为例的手机、基站以及核心网之间的信息交互的流程示意图。
图4是表示在本发明中新增的一个步骤的流程示意图。
图5是表示明文比对方式的第一种方法的基于生物特征的身份认证方法的流程示意图。
图6是表示明文比对方式中的第二种方法的基于生物特征的身份认证方法的流程示意图。
图7是表示混淆比对方式的基于生物特征的身份认证方法的流程示意图。
图8是表示模糊比对方式的第一种方法的基于生物特征的身份认证方法的流程示意图。
图9是表示明文比对方式中的第二种方法的基于生物特征的身份认证方法的流程示意图。
图10是表示混淆模糊比对方式的基于生物特征的身份认证方法的流程示意图。
图11是表示第一实施方式的基于生物特征的身份认证方法的流程示意图。
图12是表示第一实施方式的基于生物特征的身份认证系统的结构框图。
图13是表示第二实施方式的基于生物特征的身份认证方法的流程示意图。
图14是表示第二实施方式的基于生物特征的身份认证系统的结构框图。
图15是表示第三实施方式的基于生物特征的身份认证方法的流程示意图。
图16是表示第三实施方式的基于生物特征的身份认证系统的结构框图。
图17是表示第四实施方式的基于生物特征的身份认证方法的流程示意图。
图18是表示第四实施方式的基于生物特征的身份认证系统的结构框图。
图19是表示第五实施方式的基于生物特征的身份认证方法的流程示意图。
图20是表示第五实施方式的基于生物特征的身份认证系统的结构框图。
图21是表示第六实施方式的基于生物特征的身份认证方法的流程示意图。
图22是表示第六实施方式的基于生物特征的身份认证系统的结构框图。
具体实施方式
下面介绍的是本发明的多个实施例中的一些，旨在提供对本发明的基本了解。并不旨在确认本发明的关键或决定性的要素或限定所要保护的范围。
出于简洁和说明性目的，本文主要参考其示范实施例来描述本发明的原理。但是，本领域技术人员将容易地认识到，相同的原理可等效地应用于所有类型的基于生物特征的身份认证方法以及基于生物特征的身份认证系统，并且可以在其中实施这些相同的原理，以及任何此类变化不背离本专利申请的真实精神和范围。
而且，在下文描述中，参考了附图，这些附图图示特定的示范实施例。在不背离本发明的精神和范围的前提下可以对这些实施例进行电、机械、逻辑和结构上的更改。此外，虽然本发明的特征是结合若干实施/实施例的仅其中之一来公开的，但是如针对任何给定或可识别的功能可能是期望和/或有利的，可以将此特征与其他实施/实施例的一个或多个其他特征进行组合。因此，下文描述不应视为在限制意义上的，并且本发明的范围由所附权利要求及其等效物来定义。
诸如“具备”和“包括”之类的用语表示除了具有在说明书和权利要求书中有直接和明确表述的单元和步骤以外，本发明的技术方案也不排除具有未被直接 或明确表述的其它单元和步骤的情形。诸如“第一”和“第二”之类的用语并不表示单元在时间、空间、大小等方面的顺序而仅仅是作区分各单元之用。
首先，对于本发明的场景以及技术构架进行说明。
图1是表示本发明的基于生物特征的身份认证系统以及身份认证方法的场景示意图。
如图1所示，在本发明中，用户携带手机1、手机2、手机3……(“手机”对应于权利要求书中的“移动终端”，后文也将以手机为例进行说明)进入基站信号覆盖的商户(“商户区域”对应于权利要求书中的“规定区域”，后文也将以商户为例进行说明)，生物特征识别终端采集用户的生物特征并送到生物特征识别后台，另一方面，基站管理模块能够得知进入到商户所对应的基站接入的手机号码，通过生物特征识别后台与基站管理模块的交互，从基站获取接入的手机号码缩小N的范围，来锁定并缩小生物特征的搜索范围，由此，确保生物特征识别结果的准确性，完成生物特征识别。在本发明中生物特征包括但又不限于以下的任意一种或者多种的组合：人脸、指静脉、虹膜、指纹、掌纹以及声音。
图2是表示本发明的基于生物特征的身份认证系统技术构架的示意图。
如图2所示，本发明的基于生物特征的身份认证系统主要包括获基站20、基站管理模块30、生物特征识别终端40以及生物特征识别后台50。
接着，对于这些构造部分进行说明。
首先，说明基站20。
在本发明中，基站为改良型基站，用于室内商户的信号覆盖。目前，基站均可获取接入其的手机的手机号码。但是目前基站通常将获取到接入手机的信息都传统通讯协议上送核心网，且获取的手机的信息除包含手机号之外其他信息导致运营商实时获取基站接入手机号难度大，需改进现有基站。
通常基站会不断广播其位置信息，当手机进入一个新的区域后(或开机)会发现其原有位置信息和接受到广播位置信息不同，则将手机信息传送至基站，然后再将这些信息至核心网，让后台能重新登记手机位置。改良后的基站除了将手机相关信息按按传统通讯协议传送至核心网外，也会单独将手机号等必要信息发送至基站管理模块。
图3是表示以4G-LTE为例的手机、基站以及核心网之间的信息交互的流程示意图。图4是表示在本发明新增一个步骤后的流程示意图。
如图3所示，以4G-LTE为例的原有的流程如下：
1、基站广播位置信息；
2、手机收到位置信息后判断该信息与之前存储的位置是否发生变化(即是否进入新的区域)；
3-6、是一些预处理过程，具体如下：
3、RA Preamble表示随机接入索引，3的过程是向基站发送随机接入请求；
4、RA Response表示响应随机接入；
5、RRCConnection Request表示发送RRC连接建立请求；
6、建立RRC连接；
7、手机上送手机信息包括(IMEI即国际移动设备识别码、IMSI即国际移动用户识别码、手机号等)至基站；
8、基站将手机信息及位置更新请求信息传输至核心网；
9、手机、基站、核心网间交互操作完成后续操作。
在本发明中，保留原有上述的所有通信流程，但是添加一个新的步骤：即如图4所示的步骤“9”(基站将单独的手机号信息传送至基站管理模块)以及基站管理模块将与生物特征识别后台进行交互。
另一方面，为了保证效果，商户可以根据实际场景布放多台基站。
接着，说明生物特征识别终端40。
作为一个示例，生物特征识别终端40可放置于商户结账处，用于采集用户生物特征及提示生物特征识别结果。生物特征识别终端40，包括但不限于液晶显示屏、LED等提示装置，同时配套语音提醒功能，通过人性化的服务方式，为用户提供良好的支付体验。
接着，说明生物特征识别后台50。生物特征识别后台540包括生物特征识别模块51和生物特征数据库52。生物特征数据库52内保存生物特征与手机号一一对应关系。生物特征识别模块51用于将采集到的生物特征与生物特征数据库52中的生物特征一比一比对，获得相似度。并将相似度最高的N个人的手机号列表。这里，对N不做限定，可以为大于1的任意的自然数，在以下的表1中作为一个示例，取N为10。
Figure PCTCN2020110740-appb-000001
表1
最后，说明基站管理模块30。
基站管理模块30存有基站20与商户对应关系(当然，也可以是生物特征识别后台50存有该对应关系，此处以基站管理模块30即运营商存有该对应关系为例)，并维护接入基站20的手机号列表。作为基站与商户的对应关系，可以是一个商户对应于于一个基站号，也可以一个商户对应于多个基站号，或者多个商户对应于一个基站号，例如，表2中表示了商户号与基站号的对应关系以及各基站号接入的手机号码的示例。
Figure PCTCN2020110740-appb-000002
Figure PCTCN2020110740-appb-000003
表2
如上所述，本发明的一个方面的基于生物特征的身份认证系统可具备：
基站20，实时获取进入到该基站20覆盖区域的用户的手机10的手机号码，将用户的手机号码和基站标识号发送给基站管理模块50；
基站管理模块30，接收用户的手机号码和基站标识号，根据预先存储的基站标识号与商户之间的关联关系，获得进入到商户的用户的手机号码以生成第一手机号码列表，将第一手机号码列表发送至下述的生物特征识别后台50；
生物特征识别终端40，用于获取用户的生物特征；
生物特征识别后台50，包括用于预先存储用户的生物特征与手机号码之间的绑定关系的生物特征数据库51以及基于所述绑定关系获得与所述人脸识别终端40识别的用户的生物特征相似度最高的N个手机号码组成的第二手机号码列表，其中，N为大于1的自然数，另一方面，接收基站管理模块30发送来的第一手机号码列表，并将第一手机号码列表与第二手机号码列表进行比较，如果两者的交集为1个手机号码，则判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的手机号码的用户为身份认证成功用户。
这里列举了在在生物特征识别后台50进行第一手机号码里列表和第二手机号码列表的比对，作为它的变换方式，也可以在基站管理模块30进行第一手机号码里列表和第二手机号码列表的比对，即如下所述：
本发明又一个方面的基于生物特征的身份认证系统可以具备：
基站20，实时获取进入到该基站20覆盖区域的用户10的手机号码，将用户10的手机号码和基站标识号发送给下述的基站管理模块30；
基站管理模块30，从基站20接收用户的手机号码和基站标识号，根据预先存储的基站标识号与商户之间的关联关系，获得进入到商户的用户的手机号码以生成第一手机号码列表；
生物特征识别终端40，用于获取用户的生物特征；
生物特征识别后台50，包括用于预先存储用户的生物特征与手机号码之间的绑定关系的生物特征数据库51以及用于基于所述绑定关系获得与所述生物特征识别终端40识别的用户的生物特征相似度最高的N个手机号码组成的第二手机号码列表，其中，N为大于1的自然数，并将第二手机号码列表发送到基站管理模块30，
其中，基站管理模块30接收生物特征识别后台50发送来的第二手机号码列表，并将第一手机号码列表与第二手机号码列表进行比较并且将两者的交集返回到所述生物特征识别后台50，
生物特征识别后台50对于接收到的两者的交集进行判断，如果两者的交集为1个手机号码，则判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的手机号码的用户为身份认证成功用户。
如上所述，在本发明中，生物特征识别采用1：N的方案，并为了保证识别结果的准确性，通过对手机号码的筛选，将数量N控制在一定范围内。
接着，对于本发明的基于生物特征的身份认证方法进行说明。在本发明的基于生物特征的身份认证方法中，利用移动终端与基站的交互获得的信息来缩小N的范围，将识别范围动态控制在当前出现在贵区域(例如商户、交通设施等，)内的用户群体，而非全部注册用户。在以下的说明中作为“规定区域”以“商户”为例进行说明，作为移动终端以手机为例进行说明。
本发明的基于生物特征的身份认证方法整体上包括注册阶段、预处理阶段、识别阶段三个阶段：
1、注册阶段
注册阶段用户提交生物特征(例如人脸图片、指纹信息、掌纹信息、虹膜信息等)、银行卡、手机号并进行绑定。
2、预处理阶段
用户在进行生物特征识别之前会先进入商户，进入商户时用户需携带手机， 基站广播位置信息，手机上送信息更新请求及手机信息至基站，将手机号及基站号发送至基站管理模块。基站管理模块存有基站与商户的对应关系，并动态维护商户内的手机号列表，即，动态提供接入基站的第一手机号列表。
3、识别阶段
在识别阶段，识别用户的生物特征，基于用户的生物特征与移动终端号码之间预先建立的绑定关系，获得与所述生物特征相似度最高的n个移动终端号码组成的第二手机号码列表，其中，n为大于1的自然数，接着，将第一手机号码列表与第二手机号码列表进行比较，来完成生物特征识别。
对于不同场景，基站管理模块与生物特征识别后台可能都存在不暴露自己数据的需求，因此以下将说明若种不同的比对方式，以满足各方需求。
(1)明文比对
明文比对的第一种模式是由生物特征识别后台传输手机列表到基站管理模块，由基站管理模块比对并返回手机号码列表的交集，最后由生物特征识别后台再比对交集。
图5是表示明文比对方式的第一种模式的基于生物特征的身份认证方法的流程示意图。
如图5所示，在步骤S1中，生物特征识别后台获得生物特征识别终端传识别的用户的生物特征，基于用户的生物特征与手机号码之间预先建立的绑定关系，生物特征识别后台获得与所述生物特征相似度最高的n个手机号码的手机号码列表并将该手机号码列表发送到基站管理模块，其中，n为大于1的自然数。
在步骤S2中，通过用户进入到商户所相关联的基站，基站管理模块获得进入到该商户的用户的手机号码列表(该步骤可以在步骤S1之前就进行)，然后，基站管理模块比对进入商户内的手机号码列表与从生物特征识别后台发送来的相似度最高的n个用户的手机号码列表的交集，在步骤S3中将两者的交集返回到生物特征识别后台。
在步骤S4中，生物特征识别后台判断两者的交集是否为1个手机号码。若两者的交集为1个手机号码，则进入步骤S5,则去该交集为生物特征识别最终结果，即该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则进入步骤S6，将交集中生物特征相似度最高的作为生物特征识别最终结果，即将交集中生物特征相似度最高的手机号码的用户为身份认证成功用户。
作为可选方式，比对时，生物识别后台将识别出的相似度最高的n个用户的手机号进行加密运算(例如HASH等)，同样地基站管理模块也将其列表中的 手机号进行相同的加密运算，通过比对加密后的手机号码列表，能够保证生物特征识别后台不向基站管理模块暴露真实的数据，即能够保证基站管理模块不会知晓最终生物特征识别结果，即最终完成交易的人。
明文比对的第二种模式是由基站管理模块向生物特征识别后台传输手机号码列表，由生物特征识别后台进行比对手机号码列表以及比对手机号码列表的交集。
图6是表示明文比对方式中的第二种模式的基于生物特征的身份认证方法的流程示意图。
如图6所示，在步骤S11中，生物特征识别后台向基站管理模块发起获得进入商户内的手机号码列表的请求。在步骤S12中基站管理模块返回进入商户内的手机号码列表。在步骤S13，生物特征识别后台获得生物特征识别终端传识别的用户的生物特征，基于用户的生物特征与手机号码之间预先建立的绑定关系，获得与生物特征相似度最高的n个手机号码的手机号码列表，然后，生物特征识别后台比对与生物特征相似度最高的n个手机号码的手机号码列表与从基站管理模块发送来的进入商户内的手机号码列表是否具有交集。在步骤S14中判断两者的交集是否为1个手机号码，若两者的交集为1个手机号码，则进入步骤S15,判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则进入步骤S16，判断交集中生物特征相似度最高的手机号码的用户为身份认证成功用户。
作为可选的方式，与第一种模式类似，基站管理模块可将其列表中的手机号进行加密运算(例如HASH等)后进行传输，生物特征识别列表中的手机号也做相同的加密运算，完成比对。该方式能够保证生基站管理模块不暴露自己的数据。
(2)混淆比对
混淆比对的第一种模式是由生物特征识别后台传输增加了m个混淆用随机手机号码的手机列表到基站管理模块，由基站管理模块比对并返回手机号码列表的交集，最后由生物特征识别后台再比对交集。
图7是表示混淆比对方式的基于生物特征的身份认证方法的流程示意图。
如图7所示，在步骤S21中，生物特征识别后台获得生物特征识别终端传识别的用户的生物特征，基于用户的生物特征与手机号码之间预先建立的绑定关系，生物特征识别后台获得与所述生物特征相似度最高的n个手机号码的手机号码列表，将包括n个相似度高的手机号及其他随机产生的m个随机手机号打包成 一个列表发送到基站管理模块，其中，n为大于1的自然数，m为自然数。
在步骤S22中，通过用户进入到商户所相关联的基站覆盖区域，基站管理模块获得进入到该商户的用户的手机号码列表(该步骤可以在步骤S21之前就进行)，然后，基站管理模块比对进入商户内的手机号码列表与从生物特征识别后台发送来的包括相似度最高的n个用户的手机号码与m个随机手机号组成的手机号码列表，求两者的交集，在步骤S23中将两者的交集返回到生物特征识别后台。
在步骤S24中，生物特征识别后台判断两者的交集是否为1个手机号码。若两者的交集为1个手机号码，则进入步骤S25,判断该手机号码的用户为最终生物特征识别结果，即身份认证成功用户，如果两者的交集大于1个号码，则进入步骤S26，对于交集，排除m个随机手机号码之后，再将生物特征相似度最高作为最终结果，即将生物特征相似度最高的手机号码的用户作为身份认证成功用户。
混淆比对方式与明文比对方式相比，由于刻意地将m个随机手机号码混淆到相似度高的n个生物特征的手机号中，因此，基站管理模块无法获取准确的相似度高的n个生物特征的手机号。
作为可选方式，比对时，生物识别后台将识别出的相似度最高的n个用户的手机号和m个随机手机号码进行加密运算(例如HASH等)，同样地基站管理模块也将其列表中的手机号进行相同的加密运算，通过比对加密后的手机号码列表，能够保证生物特征识别后台不向基站管理模块暴露真实的数据，即能够保证基站管理模块不会知晓最终生物特征识别结果，即最终完成交易的人。
(3)模糊比对
模糊比对方式的第一种模式是生物特征识别后台不传输完整的手机号码列表而是传输手机号码中的固定位数到基站管理模块，基站管理模块比对收到的固定位数的手机号码列表和从基站获得的进入商户内的手机号码中的固定位数的手机号码列表，并返回交集到生物特征识别后台，由生物特征识别后台再对交集进行比对。
图8是表示模糊比对方式的第一种模式的基于生物特征的身份认证方法的流程示意图。
如图8所示，在步骤S31中，生物特征识别后台获得生物特征识别终端传识别的用户的生物特征，基于用户的生物特征与手机号码之间预先建立的绑定关系，生物特征识别后台获得与所述生物特征相似度最高的n个手机号码的手机号码列表，这里并不传输完整手机号，而是传输手机号的固定位数(比如前三位后 四位)发送至基站管理模块。
在步骤S32中，通过用户进入到商户所相关联的基站，基站管理模块获得进入到该商户的用户的手机号码列表(该步骤可以在步骤S31之前就进行)，这里进入到该商户的用户的手机号码列表中也同样地取手机号的固定位数(比如前三位后四位)，然后，基站管理模块比对进入商户内的手机号码列表(比如前三位后四位)与从生物特征识别后台发送来的包括相似度最高的n个用户的手机号码(比如前三位后四位)，求两者的交集，在步骤S33中将两者的交集返回到生物特征识别后台。
在步骤S34中，生物特征识别后台判断两者的交集是否为1个手机号码。若两者的交集为1个手机号码，则进入步骤S35,判断该手机号码的用户为最终生物特征识别结果，即身份认证成功用户，如果两者的交集大于1个号码，则进入步骤S36，对于交集，将生物特征相似度最高作为最终结果，即将生物特征相似度最高的手机号码的用户作为身份认证成功用户。
作为可选方式，比对时，生物识别后台将识别出的相似度最高的n个用户的手机号的固定位数(比如前三位后四位)进行加密运算(例如HASH等)，同样地基站管理模块也将其列表中的手机号的固定位数(比如前三位后四位)进行相同的加密运算。
在模糊比对方式的优势在于基站管理模块和生物特征识别后台互不能确定对方拥有的准确手机号列表。
模糊比对的第二种模式是由基站管理模块向生物特征识别后台传输手机号码列表，由生物特征识别后台进行比对手机号码列表以及比对手机号码列表的交集。
图9是表示明文比对方式中的第二种模式的基于生物特征的身份认证方法的流程示意图。
如图9所示，在步骤S41中，生物特征识别后台向基站管理模块发起获得进入商户内的手机号码列表的请求。在步骤S42中基站管理模块返回进入商户内的手机号码列表，这里不返回完整的手机号码而是手机号码的固定位数(比如前三位后四位)。在步骤S43，生物特征识别后台获得生物特征识别终端传识别的用户的生物特征，基于用户的生物特征与手机号码之间预先建立的绑定关系，获得与生物特征相似度最高的n个手机号码的手机号码列表，这里，不取完整的手机号码而是手机号码的固定位数(比如前三位后四位)。然后，生物特征识别后台比对与生物特征相似度最高的n个手机号码的手机号码列表(比如前三位后四 位)与从基站管理模块发送来的进入商户内的手机号码列表(比如前三位后四位)是否具有交集。在步骤S44中判断两者的交集是否为1个手机号码，若两者的交集为1个手机号码，则进入步骤S45,判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则进入步骤S46，判断交集中生物特征相似度最高的手机号码的用户为身份认证成功用户。
作为可选的方式，基站管理模块可将其列表中的手机号的固定位数(比如前三位后四位)进行加密运算(例如HASH等)后进行传输，生物特征识别列表中的手机号的固定位数(比如前三位后四位)也做相同的加密运算，完成比对。
该种模式的优势除了基站管理模块和生物特征识别后台互不能确定对方拥有的准确手机号列表外。基站管理模块也不会知晓最终生物特征识别结果(即最终完成交易的人)。
(4)混淆模糊比对
混淆模糊比对结合了混淆比对和模糊比对的两种方式。
图10是表示混淆模糊比对方式的基于生物特征的身份认证方法的流程示意图。
如图10所示，在步骤S51中，生物特征识别后台获得生物特征识别终端传识别的用户的生物特征，基于用户的生物特征与手机号码之间预先建立的绑定关系，生物特征识别后台获得与所述生物特征相似度最高的n个手机号码的固定位数(比如前三位后四位)的手机号码列表，将包括n个相似度高的手机号的固定位数(比如前三位后四位)及其他随机产生的m个随机手机号的固定位数(比如前三位后四位)打包成一个列表发送到基站管理模块，其中，n为大于1的自然数，m为自然数。
在步骤S52中，通过用户进入到商户所相关联的基站，基站管理模块获得进入到该商户的用户的手机号码列表(该步骤可以在步骤S51之前就进行)，仅取手机号码中的固定位数(比如前三位后四位)作为手机号码列表，然后，基站管理模块比对进入商户内的手机号码的固定位数(比如前三位后四位)的列表与从生物特征识别后台发送来的包括相似度最高的n个用户的手机号码的固定位数(比如前三位后四位)与m个随机手机号的固定位数(比如前三位后四位)组成的手机号码列表，求两者的交集，在步骤S53中将两者的交集返回到生物特征识别后台。
在步骤S54中，生物特征识别后台判断两者的交集是否为1个手机号码。若两者的交集为1个手机号码，则进入步骤S55,判断该手机号码的用户为最终生 物特征识别结果，即身份认证成功用户，如果两者的交集大于1个号码，则进入步骤S56，对于交集，排除m个随机手机号码后，再将生物特征相似度最高作为最终结果，即将生物特征相似度最高的手机号码的用户作为身份认证成功用户。
作为可选方式，比对时，生物识别后台将识别出的相似度最高的n个用户的手机号码的固定位数(比如前三位后四位)和m个随机手机号码的固定位数(比如前三位后四位)进行加密运算(例如HASH等)，同样地基站管理模块也将其列表中的手机号的固定位数(比如前三位后四位)进行相同的加密运算，通过比对加密后的手机号码列表进行身份认证。
这种方式下，除了基站管理模块和生物特征识别后台互不能确定对方拥有的准确手机号列表外，基站管理模块也不会知晓最终人脸识别结果(即最终完成交易的人)。
以下，对于本发明的基于生物特征的身份认证方法以及基于生物特征的身份认证系统的具体实施方式进行说明。
在识别之前需要进行用户注册。用户通过注册，将用户的手机号与银行卡、人脸进行绑定。在注册阶段，本发明的基于生物特征的身份认证系统采集如下信息：
(1)用户身份信息
采集用户身份信息，包括姓名、手机号、身份证号。用于注册时对上送的人脸照片进行验证和人脸识别结果的展示(脱敏)。
(2)用户人脸信息
即用户人脸照片。验证通过后入库，用作人脸识别的比对样本。
(3)银行卡信息
包括姓名、银行卡号、银行预留手机号、短信验证码等信息，用于到发卡银行验证银行卡有效性。系统将在用户进出闸机后，通过识别结果从该绑定卡片中扣费。其中，用户在注册过程中，首先采集用户身份信息，再上送人脸照片，系统将用户身份信息与人脸照片信息通过公安系统进行验证，通过后，继续采集用户银行卡信息，系统将银行卡要素送至发卡行进行验证，通过后，将采集到的用户身份信息(手机号)、人脸信息和银行卡信息进行绑定。
在以下实施方式中作为生物特征以人脸为例进行说明，然而也可以进行各种变换方，例如，在注册时，可不上送人脸，例如改为采集指静脉生物特征图像或者虹膜或者掌纹。采集指静脉生物特征图像的情况下，通过闸机时将用户手指放置在指静脉采集器上采集图像，并将图像上送，也可在数据库中进行搜索比对。
以下对于本发明的基于生物特征的身份认证方法以及基于生物特征的身份认证系统的具体实施方式进行说明。
第一实施方式(明文比对方式的第一种模式)
图11是表示第一实施方式的基于生物特征的身份认证方法的流程示意图。
如图11所示，第一实施方式的基于生物特征的身份认证方法包括下述步骤：1、用户进入商户后，手机上送LAC以及手机号信息到基站，其中，LAC是指地理位置更新信息，即当手机收到基站广播的信号，发现自己原来接受的基站信号和现在收到的广播信号不同就会上传该信息；
2、基站(由图11中位于手机和基站管理模块之间的图样表示)将手机号及基站号发送至基站管理模块(相当于运营商)；
3、基站管理模块根据基站号动态维护商户内手机号列表，手机号HASH加密；
4、人脸识别终端采集人脸；
5、脸识别终端将商户号及人脸上传至人脸识别后台；
6、人脸识别后台对人脸及人脸数据库里的人脸做1：1比对，获得相似度最高的n位的人脸的手机号，每个手机号做HASH加密；
7、人脸识别后台将n个的手机号做过HASH加密并传输至基站管理模块；
8、基站管理模块比对其维护的列表手机号的HASH值与人脸识别后台上送的手机号的HASH值，获取交集手机号码；
9、返回交集手机号(HASH值)至人脸识别后台；
10、若交集为1，则确认唯一用户，若交集大于1则交集中相似度最高的人脸为最终结果。
图12是表示第一实施方式的基于生物特征的身份认证系统的结构框图。
如图12所示，第一实施方式的基于人脸的身份认证系统具备：
基站100，实时获取进入到该基站100覆盖区域的用户的手机号码，将用户的手机号码和基站标识号发送给下述的基站管理模块101；
基站管理模块101，从基站100接收用户的手机号码和基站标识号，基于来自下述的人脸识别后台103上送的商户号并根据预先存储的基站标识号与商户号之间的关联关系，获得进入到该商户的所有用户的手机号码以生成第一手机号码列表；
人脸识别终端102，用于获取用户的人脸；
人脸识别后台103，包括：人脸数据库104，用于预先存储用户的人脸与手 机号码之间的绑定关系以及人脸识别模块105，用于基于所述绑定关系获得与所述人脸识别终端识别的用户的人脸相似度最高的n个手机号码组成的第二手机号码列表，其中，n为大于1的自然数，并将所述第二手机号码列表以及商户号发送到基站管理模块101，
其中，所述基站管理模块101接收所述人脸识别后台103发送来的所述第二手机号码列表，并将所述第一手机号码列表与所述第二手机号码列表进行比较并且将两者的交集返回到所述人脸识别后台103，人脸识别后台103的人脸识别模块105对于接收到的两者的交集进行判断，如果两者的交集为1个手机号码，则判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述人脸相似度最高的手机号码的用户为身份认证成功用户。
进一步地，基站管理模块101具备下述子模块(未图示)：
第一接收模块，用于接收从基站100发送来的进入到该基站覆盖区域的用户的手机号码和基站标识号；
基站数据库，用于预先存储的基站标识号与商户号之间的关联关系；
第二接收模块，从外部(即人脸识别后台103)接收第二手机号码列表以及商户号；
第一比对处理模块，根据所述基站数据库存储的所述关联关系，基于从所述第一接收模块接收到的用户的手机号码和基站标识号以及从所述第二接收模块接收到的商户号，获得进入到该商户的所有用户的手机号码以生成第一手机号码列表；
第二比对处理模块，将所述第一手机号码列表与所述第二手机号码列表进行比较，并获得两者的交集。
其中，可选的是，在基站管理模块101可以对从基站100上送的第一手机号码列表进行HASH加密运算，对应地，在人脸识别后台103也可以将第二手机号码列表进行HASH加密运算，这样在基站管理模块101比较HASH加密运算后的两者结果。
第二实施方式(明文比对方式的第二种模式)
图13是表示第二实施方式的基于生物特征的身份认证方法的流程示意图。
如图13所示，第二实施方式的基于生物特征的身份认证方法包括下述步骤：
1、用户进入商户后，手机上送地理位置更新信息及手机号信息至基站；
2、基站将手机号及基站号发送至基站管理模块；
3、基站管理模块根据基站号动态维护商户内手机号列表，手机号HASH加密；
4、人脸识别终端采集人脸；
5、人脸识别终端将商户号及人脸上传至人脸识别后台；
6、人脸识别后台对人脸及人脸数据库里的人脸做1：1比对，获得相似度最高的n位的人脸的手机号，每个手机号做HASH加密；
7、人脸识别后台请求基站管理模块获取商户内手机号列表；
8、基站管理模块返回商户内经过HASH加密的手机号列表至人脸识别平台；
9、人脸识别后台获取商户内手机号列表与相似度最高的n个人脸的手机号的交集，若交集为1，则确认唯一用户，若交集大于1则交集中相似度最高的人脸为最终结果；
10、人脸识别完成。
图14是表示第二实施方式的基于生物特征的身份认证系统的结构框图。
如图14所示，第二实施方式的基于人脸的身份认证系统，具备：
基站200，实时获取进入到该基站覆盖区域的用户的手机号码，将用户的手机号码和基站标识号发送给下述的基站管理模块201；
基站管理模块201，用于从基站200接收用户的手机号码和基站标识号，根据预先存储的基站标识号与商户之间的关联关系，获得进入到所述商户的所有用户的手机号码以生成第一手机号码列表，并且将所述第一手机号码列表发送至下述的人脸识别后台202；
人脸识别终端202，用于获取用户的人脸；
人脸识别后台203，包括：人脸数据库204，用于预先存储用户的人脸与手机号码之间的绑定关系以及人脸识别模块205，用于基于所述绑定关系获得与所述人脸识别终端识别的用户的人脸相似度最高的n个手机号码组成的第二手机号码列表，其中，n为大于1的自然数，另一方面，接收基站管理模块201发送来的所述第一手机号码列表，并将所述第一手机号码列表与所述第二手机号码列表进行比较，如果两者的交集为1个手机号码，则判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述人脸相似度最高的手机号码的用户为身份认证成功用户。
其中，可选的是，在基站管理模块101可以对从基站100上送的第一手机号码列表进行HASH加密运算，对应地，在人脸识别后台103也可以将第二手机号码列表进行HASH加密运算并比较HASH加密运算后的两者。
第三实施方式(混淆比对方式的第一种模式)
图15是表示第三实施方式的基于生物特征的身份认证方法的流程示意图。
如图15所示，第三实施方式的基于生物特征的身份认证方法包括下述步骤：
1、用户进入商户后，手机上送地理位置更新信息及手机号信息至基站；
2、基站将手机号及基站号发送至基站管理模块；
3、基站管理模块根据基站号动态维护商户内手机号列表，手机号HASH加密；
4、人脸识别终端采集人脸；
5、人脸识别终端将商户号及人脸上传至人脸识别后台；
6、人脸识别后台对人脸及人脸数据库里的人脸做1：1比对，获得相似度最高的n位的人脸的手机号，同时随机生成m个混淆用手机号形成列表，每个手机号做HASH加密，其中，m为自然数；
7、人脸识别后台将经过HASH加密的n位的手机号和m个混淆用手机号传输至基站管理模块；
8、基站管理模块比对其维护的手机号码列表与人脸识别后台上送的手机号列表，获取交集；
9、返回交集至人脸识别后台；
10、若交集为1，则确认唯一用户，若交集大于1则交集中相似度最高的人脸为最终结果；
11、人脸识别完成。
图16是表示第三实施方式的基于生物特征的身份认证系统的结构框图。
如图16所示，第三实施方式的基于生物特征的身份认证系统具备：
基站300，实时获取进入到该基站覆盖区域的用户的手机号码，将用户的手机号码和基站标识号发送给下述的基站管理模块301；
基站管理模块301，从所述基站300接收用户的手机号码和基站标识号，根据预先存储的基站标识号与商户的商户号之间的关联关系，获得进入到商户的所有用户的手机号码以生成第一手机号码列表；
人脸识别终端302，用于获取用户的人脸；
人脸识别后台303，包括：人脸数据库304，用于预先存储用户的人脸与手机号码之间的绑定关系以及人脸识别模块305，用于基于所述绑定关系获得与所述人脸识别终端识别的用户的人脸相似度最高的n个手机号码组成的第二手机号 码列表，其中，n为大于1的自然数，其中使得第二手机号码列表进一步包含被随机生成m个混淆用手机号码构成，其中m为自然数，并将所述第二手机号码列表发送到所述基站管理模块301。
其中，基站管理模块301接收人脸识别后台303发送来的第二手机号码列表，并将第一手机号码列表与第二手机号码列表进行比较并且将两者的交集返回到所述人脸识别后台303。人脸识别后台303中的人脸识别模块305对于接收到的两者的交集，先排除m个混淆用手机号，然后进行判断，如果两者的交集为1个手机号码，则判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述人脸相似度最高的手机号码的用户为身份认证成功用户。
其中，可选的是，在基站管理模块301可以对从第一手机号码列表进行HASH加密运算，对应地，在人脸识别后台303也将第二手机号码列表进行HASH加密运算，这样在基站管理模块301比较HASH加密运算后的两者结果。
第四实施方式(模糊比对方式的第一种模式)
图17是表示第四实施方式的基于生物特征的身份认证方法的流程示意图。在该实施方式中采用HASH加密方法，并且取手机号前3位后4位模糊处理。
如图17所示，第四实施方式的基于生物特征的身份认证方法包括下述步骤：
1、用户进入商户后，手机上送地理位置更新信息及手机号信息至基站；
2、基站将手机号及基站号发送至基站管理模块；
3、基站管理模块根据基站号动态维护商户内手机号列表，取手机号HASH前三后四位加密；
4、人脸识别终端采集人脸；
5、人脸识别终端将商户号及人脸上传至人脸识别后台；
6、人脸识别后台对人脸及人脸数据库里的人脸做1：1比对，获得相似度最高的n个的人脸的手机号，对每个手机号的前三后四位做HASH加密，n为自然数；
7、人脸识别后台将做过HASH加密的手机号(前三后四位)并传输至基站管理模块；
8、基站管理模块比对其维护的列表手机号与人脸识别后台上送的手机号列表，获取两者的交集；
9、将交集(HASH值)返回至人脸识别后台；
10、若交集为1，则确认唯一用户，若交集大于1则交集中相似度最高的人脸为最终结果；
11、人脸识别完成。
图18是表示第四实施方式的基于生物特征的身份认证系统的结构框图。
如图18所示，第四实施方式的基于生物特征的身份认证系统具备：
基站400，实时获取进入到该基站覆盖区域的用户的手机号码，将用户的手机号码和基站标识号发送给下述的基站管理模块401；
基站管理模块401，从所述基站300接收用户的手机号码和基站标识号，根据预先存储的基站标识号与商户号之间的关联关系，获得进入到商户的所有用户的手机号码并且取手机号码的前三四后位来生成第一手机号码列表；
人脸识别终端402，用于获取用户的人脸；
人脸识别后台403，包括：人脸数据库404，用于预先存储用户的人脸与手机号码之间的绑定关系以及人脸识别模块405，用于基于所述绑定关系获得与所述人脸识别终端识别的用户的人脸相似度最高的n个手机号码并且取这些手机号码前三四后位来组成第二手机号码列表，其中，n为大于1的自然数，并将所述第二手机号码列表和商户号发送到所述基站管理模块401。
其中，基站管理模块401接收人脸识别后台403发送来的第二手机号码列表，并将第一手机号码列表与第二手机号码列表进行比较并且将两者的交集返回到所述人脸识别后台403。人脸识别后台403中的人脸识别模块405对于接收到的两者的交集进行判断，如果两者的交集为1个手机号码，则判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述人脸相似度最高的手机号码的用户为身份认证成功用户。
其中，基站管理模块401包括(未图示)：
第一接收模块，用于接收从基站400发送来的进入到该基站覆盖区域的用户的手机号码和基站标识号；
基站数据库，用于预先存储的基站标识号与商户的商户号之间的关联关系；
第一比对处理模块，基于所述基站数据库存储的所述关联关系和所述第一接收模块接收到的用户的手机号码和基站标识号，获得进入到所述商户的所有用户的手机号码并取手机号码的前三四后位以生成第一手机号码列表；
第二接收模块，从外部(即人脸识别后台403)接收第二手机号码列表，其中，所述第二手机号码列表由与用户的生物特征相似度最高的n个手机号码并取手机号码的前三四后位来组成，其中，n为大于1的自然数；
第二比对处理模块，将所述第一手机号码列表与所述第二手机号码列表进行比较，并获得两者的交集。
其中，可选的是，在基站管理模块401可以对第一手机号码列表进行HASH加密运算，对应地，在人脸识别后台403也将第二手机号码列表进行HASH加密运算，这样在基站管理模块401比较HASH加密运算后的两者结果。
第五实施方式(模糊比对方式的第二种模式)
图19是表示第五实施方式的基于生物特征的身份认证方法的流程示意图。在本实施方式中，采用HASH加密方法，并且取手机号前三后四位进行模糊处理。
如图19所示，第二实施方式的基于生物特征的身份认证方法包括下述步骤：
1、用户进入商户后，手机上送地理位置更新信息及手机号信息至基站；
2、基站将手机号及基站号发送至基站管理模块；
3、基站管理模块根据基站号动态维护商户内手机号列表，对手机号前三后四位HASH加密；
4、人脸识别终端采集人脸；
5、人脸识别终端将商户号及人脸上传至人脸识别后台；
6、人脸识别后台对人脸及人脸数据库里的人脸做1：1比对，获得相似度最高的n位的人脸的手机号，每个手机号前三后四位做HASH加密；
7、人脸识别后台请求基站管理模块获取商户内手机号列表；
8、基站管理模块返回商户内经过HASH加密的手机号前三后四位列表至人脸识别平台；
9、人脸识别后台获取商户内手机号列表与相似度最高的n个人脸的手机号的交集，若交集为1，则确认唯一用户，若交集大于1则交集中相似度最高的人脸为最终结果。
10、人脸识别完成。
图20是表示第五实施方式的基于生物特征的身份认证系统的结构框图。
如图20所示，第五实施方式的基于人脸的身份认证系统，具备：
基站600，实时获取进入到该基站覆盖区域的用户的手机号码，将用户的手机号码和基站标识号发送给下述的基站管理模块601；
基站管理模块601，用于从基站600接收用户的手机号码和基站标识号，根据预先存储的基站标识号与商户的商户号之间的关联关系，获得进入到所述商户的所有用户的手机号码并取手机号前三后四位进行模糊处理以生成第一手机 号码列表，并且将所述第一手机号码列表发送至下述的人脸识别后台602；
人脸识别终端602，用于获取用户的人脸；
人脸识别后台603，包括：人脸数据库604，用于预先存储用户的人脸与手机号码之间的绑定关系以及人脸识别模块505，用于基于所述绑定关系获得与所述人脸识别终端识别的用户的人脸相似度最高的n个手机号码并取手机号前三后四位进行模糊处理后组成第二手机号码列表，其中，n为大于1的自然数，另一方面，接收基站管理模块501发送来的所述第一手机号码列表，并将所述第一手机号码列表与所述第二手机号码列表进行比较，如果两者的交集为1个手机号码，则判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述人脸相似度最高的手机号码的用户为身份认证成功用户。
其中，可选的是，在基站管理模块501可以对第一手机号码列表进行HASH加密运算，对应地，在人脸识别后台503将第二手机号码列表进行HASH加密运算并比较HASH加密运算后的两者。
第六实施方式(混淆模糊比对方式)
图21是表示第六实施方式的基于生物特征的身份认证方法的流程示意图。在本实施方式中，采用HASH加密方法，并且取手机号前三后四位进行模糊处理。
如图21所示，第六实施方式的基于生物特征的身份认证方法包括下述步骤：
1、用户进入商户后，手机上送地理位置更新信息及手机号信息至基站；
2、基站将手机号及基站号发送至基站管理模块；
3、基站管理模块根据基站号动态维护商户内手机号列表，手机号前三后四位做HASH加密；
4、人脸识别终端采集人脸；
5、人脸识别终端将商户号及人脸上传至人脸识别后台；
6、人脸识别后台对人脸及人脸数据库里的人脸做1：1比对，获得相似度最高的n位的人脸的手机号，同时随机生成m个混淆用手机号形成列表，每个手机号前三后四位做HASH加密，m为自然数；
7、人脸识别后台将做过HASH加密的m个手机号及n个手机号并传输至基站管理模块；
8、基站管理模块比对其维护的列表手机号与人脸识别后台上送的手机号列表，获取交集手机号的HASH值；
9、返回交集手机号的HASH值至人脸识别后台；
10、若交集为1，则确认唯一用户，若交集大于1则先排除m个混淆用手机号码，然后判断交集中相似度最高的人脸为最终结果；
11.人脸识别完成。
图22是表示第六实施方式的基于生物特征的身份认证系统的结构框图。
如图22所示，第五实施方式的基于人脸的身份认证系统，具备：
基站600，实时获取进入到该基站覆盖区域的用户的手机号码，将用户的手机号码和基站标识号发送给下述的基站管理模块601；
基站管理模块601，从所述基站300接收用户的手机号码和基站标识号，根据预先存储的基站标识号与商户号之间的关联关系，获得进入到商户的所有用户的手机号码并获取手机号码的前三四后位来生成第一手机号码列表；
人脸识别终端602，用于获取用户的人脸；
人脸识别后台603，包括：人脸数据库604，用于预先存储用户的人脸与手机号码之间的绑定关系以及人脸识别模块605，用于基于所述绑定关系获得与所述人脸识别终端识别的用户的人脸相似度最高的n个手机号码并且取这些手机号码前三四后位来组成第二手机号码列表，其中，n为大于1的自然数，并添加m个混淆用手机号码而构成第二手机号码列表，将所述第二手机号码列表和商户号发送到所述基站管理模块601，其中m为自然数。
其中，基站管理模块601接收人脸识别后台603发送来的商户号，将第一手机号码列表与第二手机号码列表进行比较并且将两者的交集返回到所述人脸识别后台603。
人脸识别后台603中的人脸识别模块605对于接收到的两者的交集，首先排除m个混淆用收集号码，然后进行判断，如果两者的交集为1个手机号码，则判断该手机号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述人脸相似度最高的手机号码的用户为身份认证成功用户。
其中，基站管理模块601包括(未图示)：
第一接收模块，用于接收从基站600发送来的进入到该基站覆盖区域的用户的手机号码和基站标识号；
基站数据库，用于预先存储的基站标识号与商户的商户号之间的关联关系；
第一比对处理模块，基于所述基站数据库存储的所述关联关系和所述第一接收模块接收到的用户的手机号码和基站标识号，获得进入到所述商户的所有用户的手机号码并取手机号码的前三四后位以生成第一手机号码列表；
第二接收模块，从外部(即人脸识别后台603)接收第二手机号码列表， 其中，所述第二手机号码列表由与用户的生物特征相似度最高的n个手机号码以及m个混淆用手机号码构成并取手机号码的前三四后位，其中，n为大于1的自然数；
第二比对处理模块，将所述第一手机号码列表与所述第二手机号码列表进行比较，并获得两者的交集。
其中，可选的是，在基站管理模块601可以对第一手机号码列表进行HASH加密运算，对应地，在人脸识别后台603也将第二手机号码列表进行HASH加密运算，这样在基站管理模块601比较HASH加密运算后的两者结果。
如上所述，根据本发明的基于生物特征的身份认证方法以及基于生物特征的身份认证系统，基站可以获取用户手机号(基站可以是宏基站也可是小基站)，可利用基站管理模块达到缩小人脸识别N的范围。由此，用户可以在开放式的环境里使用1：N人脸识别，1：N人脸识别的应用场景大大增多。同时用户只需要携带手机，不需要额外的操作就可以完成1：N人脸识别。
本发明还提供一种计算机可读介质，其上存储有计算机程序，其特征在于，该计算机程序被处理器执行时实现上述的基于生物特征的身份认证方法。
本发明还提供一种计算机设备，包括存储器、处理器以及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现上述的基于生物特征的身份认证方法。
以上，通过参考根据本发明实施方式的组件的构造框图以及方法流程图图来描述本发明。将理解这些流程图说明和/或框图的每个框、以及流程图说明和/或框图的组合可以由计算机程序指令来实现。
例如，可以将这些计算机程序指令提供给通用计算机、专用计算机或其它可编程数据处理设备的处理器以构成机器，以便由计算机或其它可编程数据处理设备的处理器执行的这些指令创建用于实施这些流程图和/或框和/或一个或多个流程框图中指定的功能/操作的部件。
例如，也可以将这些计算机程序指令加载到计算机或其它可编程数据处理器上以使一系列的操作步骤在计算机或其它可编程处理器上执行，以便构成计算机实现的进程，以使计算机或其它可编程数据处理器上执行的这些指令提供用于实施此流程图和/或框图的一个或多个框中指定的功能或操作的步骤。还应该注意在一些备选实现中，框中所示的功能/操作可以不按流程图所示的次序来发生。
以上例子主要说明了基于生物特征的身份认证方法以及基于生物特征的身份认证系统。尽管只对其中一些本发明的具体实施方式进行了描述，但是本领域 普通技术人员应当了解，本发明可以在不偏离其主旨与范围内以许多其他的形式实施。因此，所展示的例子与实施方式被视为示意性的而非限制性的，在不脱离如所附各权利要求所定义的本发明精神及范围的情况下，本发明可能涵盖各种的修改与替换。

Claims (26)

  1. 一种基于生物特征的身份认证方法，该方法是基于用户的生物特征以及用户所携带的移动终端进行身份认证的方法，其特征在于，包括下述步骤：
    第一移动终端号码列表生成步骤，通过用户进入到规定区域所相关联的基站获得进入到该规定区域的所有的用户的移动终端号码以生成第一移动终端号码列表；第二移动终端号码列表生成步骤，识别用户的生物特征，基于用户的生物特征与移动终端号码之间预先建立的绑定关系，获得与所述生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表，其中，n为大于1的自然数；以及比较步骤，将所述第一移动终端号码列表与所述第二移动终端号码列表进行比较，如果两者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的移动终端号码的用户为身份认证成功用户。
  2. 如权利要求1所述的基于生物特征的身份认证方法，其特征在于，
    在所述第一移动终端号码列表生成步骤中，对于所述进入到该规定区域的所有的用户的移动终端号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
    在所述第二移动终端号码列表生成步骤中，对于所述相似度最高的N个移动终端号码进一步进行所述规定的加密运算以生成所述第二移动终端号码列表。
  3. 如权利要求1所述的基于生物特征的身份认证方法，其特征在于，
    在所述第二移动终端号码列表生成步骤中，识别用户的生物特征，基于用户的生物特征与移动终端号码之间预先建立的绑定关系，获得与所述生物特征相似度最高的n个移动终端号码，同时随机生成m个混淆用移动终端号码，所述n个移动终端号码和所述m个混淆用移动号码组成所述第二移动终端号码列表，其中m为自然数。
  4. 如权利要求3所述的基于生物特征的身份认证方法，其特征在于，
    在所述第一移动终端号码列表生成步骤中，对于所述进入到该规定区域的所有的 用户的移动终端号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
    在所述第二移动终端号码列表生成步骤中，对于所述n个移动终端号码和所述m个混淆用移动号码进一步进行所述规定的加密运算生成所述第二移动终端号码列表。
  5. 如权利要求1所述的基于生物特征的身份认证方法，其特征在于，
    在所述第一移动终端号码列表生成步骤中，对于所述进入到该规定区域的所有的用户的移动终端号码的每一个，采集移动终端号码中的部分规定位置的号码以生成所述第一移动终端号码列表，
    在所述第二移动终端号码列表生成步骤中，对于所述相似度最高的n个移动终端号码的每一个，采集移动终端号码中的相同的部分规定位置的号码以生成所述第二移动终端号码列表。
  6. 如权利要求5所述的基于生物特征的身份认证方法，其特征在于，
    在所述第一移动终端号码列表生成步骤中，对于所述采集的移动终端号码中的部分规定位置的号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
    在所述第二移动终端号码列表生成步骤中，对于所述采集的移动终端号码中的所述部分规定位置的号码进一步进行规定的加密算法以生成所述第二移动终端号码列表。
  7. 如权利要求1所述的基于生物特征的身份认证方法，其特征在于，
    在所述第一移动终端号码列表生成步骤中，对于所述进入到该规定区域的所有的用户的移动终端号码的每一个，采集移动终端号码中的部分规定位置的号码以生成所述第一移动终端号码列表，
    在所述第二移动终端号码列表生成步骤中，获得与所述生物特征相似度最高的n个移动终端号码，同时随机生成m个混淆用移动终端号码，对于所述n个移动终端号码和所述m个混淆用移动号码的每一个，采集移动终端号码中的所述部分规定位置的号码以生成所述第二移动终端号码列表。
  8. 如权利要求7所述的基于生物特征的身份认证方法，其特征在于，
    在所述第一移动终端号码列表生成步骤中，对于所述采集的移动终端号码中的部 分规定位置的号码进一步进行规定的加密算法以生成所述第一移动终端号码列表，
    在所述第二移动终端号码列表生成步骤中，所述采集的移动终端号码中的相同的部分规定位置的号码进一步进行规定的加密算法以生成所述第二移动终端号码列表。
  9. 如权利要求1～8任意一项所述的基于生物特征的身份认证方法，其特征在于，
    所述生物特征包括下述的任意一种或者多种的组合：人脸、指静脉、虹膜、指纹、掌纹以及声音。
  10. 如权利要求1～8任意一项所述的基于生物特征的身份认证方法，其特征在于，
    所述规定区域是商户、交通设施、大楼、商业区。
  11. 如权利要求1～8任意一项所述的基于生物特征的身份认证方法，其特征在于，
    所述规定区域与所述基站之间预先设置对应关联关系，
    所述规定区域与所述基站之间的所述对应关联关系包括下述任意一种：
    一个述规定区域与一个基站对应；
    一个基站与多个规定区域对应；以及
    多个述规定区域户与一个基站对应。
  12. 一种基于生物特征的身份认证系统，其特征在于，具备：
    基站，实时获取进入到该基站覆盖区域的用户的移动终端号码，将用户的移动终端号码和基站标识号发送给下述的基站管理模块；
    基站管理模块，接收用户的移动终端号码和基站标识号，根据预先存储的基站标识号与规定区域之间的关联关系，获得进入到所述规定区域的所有用户的移动终端号码以生成第一移动终端号码列表，将所述第一移动终端号码列表发送至下述的生物特征识别后台；
    生物特征识别终端，用于获取用户的生物特征；
    生物特征识别后台，用于预先存储用户的生物特征与移动终端号码之间的绑定关系，基于所述绑定关系获得与所述生物特征识别终端识别的用户的生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表，其中，n为大于1的自然数，另一方面，接收所述基站管理模块发送来的所述第一移动终端号码列表，并将所述第一移动终端号码列表与所述第二移动终端号码列表进行比较，如果两 者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的移动终端号码的用户为身份认证成功用户。
  13. 一种生物特征识别后台，其特征在于，具备：
    生物特征数据库，用于预先存储用户的生物特征与移动终端号码之间的绑定关系；
    接收模块，从外部接收用户的生物特征，另一方面，从外部接收进入到规定区域的所有用户的移动终端号码构成的第一移动终端号码列表；
    生物特征识别模块，基于所述生物特征数据库中预先存储的绑定关系获得与所述接收模块接收的用户的生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表，其中，n为大于1的自然数，另一方面，并将所述第一移动终端号码列表与所述第二移动终端号码列表进行比较，如果两者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的移动终端号码的用户为身份认证成功用户。
  14. 如权利要求13所述的生物特征识别后台，其特征在于，
    所述接收模块从外部接收对进入到规定区域的所有用户的移动终端号码进行规定的加密运算后生成的第一移动终端号码列表，
    所述生物特征识别模块对于所述相似度最高的n个移动终端号码进一步进行所述规定的加密运算以生成所述第二移动终端号码列表。
  15. 如权利要求13所述的生物特征识别后台，其特征在于，
    所述生物特征识别模块进一步随机生成m个混淆用移动终端号码，由所述n个移动终端号码和所述m个混淆用移动号码组成所述第二移动终端号码列表。
  16. 如权利要求13所述的生物特征识别后台，其特征在于，
    所述接收模块从外部接收对于进入到规定区域的所有用户的移动终端号码的每一个采集移动终端号码中的部分规定位置的号码而生成的所述第一移动终端号码列表，
    所述生物特征识别模块进一步对于所述相似度最高的n个移动终端号码的每一个，采集移动终端号码中的所述部分规定位置的号码以生成所述第二移动终端号 码列表。
  17. 如权利要求13所述的生物特征识别后台，其特征在于，
    所述接收模块从外部接收对于进入到规定区域的所有用户的移动终端号码的每一个采集移动终端号码中的部分规定位置的号码而生成的所述第一移动终端号码列表，
    所述生物认证模块获得与所述生物特征相似度最高的n个移动终端号码，同时随机生成m个混淆用移动终端号码，对于所述n个移动终端号码和所述m个混淆用移动号码的每一个采集移动终端号码中的相同的部分规定位置的号码以生成所述第二移动终端号码列表。
  18. 如权利要求17所述的生物特征识别后台，其特征在于，
    所述接收模块从外部接收对于进入到规定区域的所有用户的移动终端号码的每一个采集移动终端号码中的部分规定位置的号码并进行规定的加密算法而生成的所述第一移动终端号码列表，
    所述生物认证模块对于所述n个移动终端号码和所述m个混淆用移动号码的每一个采集移动终端号码中的相同的部分规定位置的号码进行规定的加密算法以生成所述第二移动终端号码列表。
  19. 一种基于生物特征的身份认证系统，其特征在于，具备：
    基站，实时获取进入到该基站覆盖区域的用户的移动终端号码，将用户的移动终端号码和基站标识号发送给下述的基站管理模块；
    基站管理模块，从所述基站接收用户的移动终端号码和基站标识号，根据预先存储的基站标识号与规定区域之间的关联关系，获得进入到所述规定区域的所有用户的移动终端号码以生成第一移动终端号码列表；
    生物特征识别终端，用于获取用户的生物特征；
    生物特征识别后台，用于预先存储用户的生物特征与移动终端号码之间的绑定关系，基于所述绑定关系获得与所述生物特征识别终端识别的用户的生物特征相似度最高的n个移动终端号码组成的第二移动终端号码列表，其中，n为大于1的自然数，并将所述第二移动终端号码列表发送到所述基站管理模块，
    其中，所述基站管理模块接收所述生物特征识别后台发送来的所述第二移动终端号码列表，并将所述第一移动终端号码列表与所述第二移动终端号码列表进行比 较并且将两者的交集返回到所述生物特征识别后台，
    所述生物特征识别后台对于接收到的两者的交集进行判断，如果两者的交集为1个移动终端号码，则判断该移动终端号码的用户为身份认证成功用户，如果两者的交集大于1个号码，则判断交集中所述生物特征相似度最高的移动终端号码的用户为身份认证成功用户。
  20. 一种基站管理模块，其特征在于，具备：
    第一接收模块，用于接收从基站发送来的进入到该基站覆盖区域的用户的移动终端号码和基站标识号；
    基站数据库，用于预先存储的基站标识号与规定区域之间的关联关系；
    第一比对处理模块，基于所述基站数据库存储的所述关联关系和所述第一接收模块接收到的用户的移动终端号码和基站标识号，获得进入到所述规定区域的所有用户的移动终端号码以生成第一移动终端号码列表；
    第二接收模块，从外部接收第二移动终端号码列表，其中，所述第二移动终端号码列表由与用户的生物特征相似度最高的n个移动终端号码组成，其中，n为大于1的自然数；
    第二比对处理模块，将所述第一移动终端号码列表与所述第二移动终端号码列表进行比较，并获得两者的交集。
  21. 如权利要求20所述的基站管理模块，其特征在于，
    所述第一比对处理模块对于获得的所述进入到该规定区域的所有的用户的移动终端号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
    所述第二移动终端号码列表是由对于所述相似度最高的n个移动终端号码进一步进行所述规定的加密运算而构成的。
  22. 如权利要求20所述的基站管理模块，其特征在于，
    所述第二移动终端号码列表是由与所述生物特征相似度最高的n个移动终端号码和被随机生成m个混淆用移动终端号码构成，其中M为自然数。
  23. 如权利要求22所述的基站管理模块，其特征在于，
    所述第一比对处理模块对于所述进入到该规定区域的所有的用户的移动终端号码进一步进行规定的加密运算以生成所述第一移动终端号码列表，
    所述第二移动终端号码列表是由对于所述n个移动终端号码和所述m个混淆用移 动号码进一步进行所述规定的加密运算后而生成的移动终端号码列表。
  24. 如权利要求20所述的基于生物特征的基站管理模块，其特征在于，
    所述第一比对处理模块对于所述进入到该规定区域的所有的用户的移动终端号码的每一个，采集移动终端号码中的部分规定位置的号码以生成所述第一移动终端号码列表，
    所述第二移动终端号码列表是对于所述相似度最高的n个移动终端号码的每一个，采集移动终端号码中的相同的部分规定位置的号码而生成的移动终端号码列表。
  25. 一种计算机可读介质，其上存储有计算机程序，其特征在于，
    该计算机程序被处理器执行时实现权利要求1～11任意一项所述的基于生物特征的身份认证方法。
  26. 一种计算机设备，包括存储器、处理器以及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现权利要求1～11任意一项所述的基于生物特征的身份认证方法。
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