CN108306738A - A kind of method and system of identification identity - Google Patents
A kind of method and system of identification identity Download PDFInfo
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- CN108306738A CN108306738A CN201711451847.1A CN201711451847A CN108306738A CN 108306738 A CN108306738 A CN 108306738A CN 201711451847 A CN201711451847 A CN 201711451847A CN 108306738 A CN108306738 A CN 108306738A
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- 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
- H04L9/3242—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 involving keyed hash functions, e.g. message authentication codes [MACs], CBC-MAC or HMAC
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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
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
- H04L63/0442—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload wherein the sending and receiving network entities apply asymmetric encryption, i.e. different keys for encryption and decryption
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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
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- 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
- H04L9/3226—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 a predetermined code, e.g. password, passphrase or PIN
- H04L9/3231—Biological data, e.g. fingerprint, voice or retina
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Abstract
The invention discloses a kind of method and system of identification identity.Wherein, the method for the identification identity, including：The perception for reading host's identity ciphertext and host characterizes source, decrypts host's identity ciphertext, and the perception that host is extracted according to identity characterizes bottom, and the perception characterization source at the perception characterization bottom and host that compare host obtains qualification result；The system of the identification identity, including：Front-end application and background service program, the front-end application includes user interface section, Information reading unit, encryption unit, and the background service program includes Identification Service center cell, encryption/decryption element, pattern recognition unit, data storage cell.Method and system through the invention solve the identity document in daily communication using it is existing it is not convenient, easily by it is counterfeit, private information leakage, differentiate the problems such as difficult, prevent false evidence or the certificate that claims the identity of others fraudulently cause social danger.
Description
Technical field
The present invention relates to mobile Internet fields, more particularly to mobile Internet field identification identity process and be
System.
Background technology
The tradition card body such as identity card, employee's card, driver's license, diploma, certification is that members of society progress social activities must
The information of indispensable part, tradition card body is that full disclosure is transparent and include important private information, is existed including carrying
The ease of use issues such as inconvenient, inconvenient to use are especially easy there is also hard to tell whether it is true or false, imitated, are easy to be falsely used, private information
The serious safeties loophole problems such as leakage.Although with the development of electronic information technology with the development of digital certificate technique, it is mutual
Connected network communication both sides carry out the new means that provide of authentication, but due to the professional of digital certificate and using numerous
Trivial, it is difficult to widely dispose and apply, tradition card body is also developing towards chip card direction, but due to there was only dedicated unit
Chip card information can be read, therefore, it is difficult to make the overall arrangement for the whole people use, still there is also papery tradition demonstrate,prove body the problem of.Tradition
The security breaches problem of card body is easy to be used by people, and especially private information leakage, certificate are falsely used and copied etc. and seriously affect
Normal civil order, causes great harm to society.
Mode identification technology is exactly close by the means such as computer and optics, acoustics, electronic sensor and Principle of Statistics
Combination is cut, identity is carried out using the perception characteristics (such as fingerprint, face picture, iris, eyeprint, person's handwriting, sound etc.) inside and outside things
Identification.Biological characteristic pattern recognition system is sampled biological Perception Features, extracts its unique feature and is converted to
Digital code feature is identified using these features.Such as：Fingerprint refers to the convex recessed injustice of the positive surface skin of finger tips of people
The streakline of generation, the different line type of the regular arrangement form of streakline, starting point, terminal, binding site and the bifurcation of streakline, referred to as
The details of fingerprint, fingerprint recognition refers to be differentiated by comparing the details of different fingerprints.Face picture (face
Portion, face) identification from the face pictures of human body looks or head portrait photo face as feature, by comparing or characteristic of division point be identified
Or differentiate.
Quick Response Code (2-dimensional code) refers to that another dimension is expanded on the basis of bar code with readable
Property bar code, by image input device or photoelectric scanning device automatically identifying and reading information included in it, it is with certain spy
Fixed geometric figure is according to certain rules in the chequered with black and white graphic recording data symbol information of plane distribution；In code compilation
On dexterously using the concept for constituting " 0 " of computer-internal logical foundations, " 1 " bit stream, use several and binary system phase
Corresponding geometrical body indicates word numerical information.Common Quick Response Code code system standard has PDF417, QR Code, Code
49, Code 16K, Code One etc. lead to since Quick Response Code has the characteristics that capacity is big, fault-tolerant ability is strong, it is easy to read
Crossing Quick Response Code transmission exchange data becomes very simple and easy.
In order to solve the problems, such as that above-mentioned tradition card body using inconvenient to use and security breaches under especially line, builds a peace
Full harmonious society living environment, protects members of society legitimate rights and interests not occupied, the present invention provides a kind of method and system, is doing
Safe and reliable anti-fake or easy distinctive feature is provided on the basis of good private information protection, the carrying of body is demonstrate,proved to existing tradition or makes
With the method or approach for providing more facility and safety.
Invention content
In view of the profit and security risk inconvenient for use present in above-mentioned existing tradition card body, the purpose of the embodiment of the present invention
It is, it is advanced using the devices such as existing widely used common mobile terminal, computer and existing communication internet, use
Algorithm for pattern recognition and information safety key algorithm realize a kind of method and system of identification identity, for solving traditional identity
Identify that the existing carrying of application is easily revealed using identity document trouble, private information, easily falsely used imitated, discrimination identification difficulty
The problems such as.
Above-mentioned purpose is achieved through the following technical solutions：
An embodiment of the present invention provides a kind of methods of identification identity, which is characterized in that including：Encrypt the identity mark of host
It is identity ciphertext to know, and reads the identity ciphertext of host, reads the perception characterization source of host, decrypts the identity mark of host
Know ciphertext, the perception that host is extracted according to the ciphertext of identity or identity characterizes bottom, compares the perception characterization bottom of host
Qualification result, the result of output identification success or failure are obtained with the perception characterization source of host.
Above-mentioned host can also be vehicle, house property and other items with members of society such as natural person, organizations.It is above-mentioned
Identity include but not limited to the one of which or multinomial such as title, licence number, title includes organization name, name etc.,
Licence number includes identification number, passport number, organization mechanism code, vehicle motor number, license plate number etc..
The identity of above-mentioned encryption host is that identity ciphertext can also include further being calculated using symmetric key
The identity of method encryption host is identity ciphertext or the use of the identity of asymmetric key algorithm encryption host is body
The digital digest value that part mark ciphertext or hash algorithm (HASH) calculate the identity of host is identity ciphertext.
The identity ciphertext of above-mentioned reading host can further include：Using including camera, electronics barcode scanning gun
Quick Response Code is read in equal Optical devices scanning, and translation Quick Response Code obtains the identity ciphertext of host.
The perception characterization source of above-mentioned reading host can further include：Host is absorbed using Optical devices such as cameras
Face picture or using the audio units such as microphone listen to host sound using fingerprint device obtain host fingerprint or use
The Optical devices such as camera absorb the one of which or multinomial such as iris or the eyeprint of host.
The identity ciphertext of above-mentioned reading host and the perception characterization source of above-mentioned reading host do not have apparent sequential
Relationship, can be front and back each other.
The identity ciphertext of above-mentioned decryption host includes：The identity that host is decrypted using symmetric key algorithm is close
Text or the identity ciphertext that host is decrypted using asymmetric key algorithm, wherein when identity ciphertext is that algorithm calculates place
When the digital digest value of main identity, this step is optional step.
The above-mentioned perception characterization bottom that host is extracted according to identity includes：According to the number of identity or identity
Word abstract ciphertext extracts the perception characterization bottom of host from background data base or extracts place from remote service center according to identity
Main perception characterizes bottom or extracts the perception characterization bottom of host from local file according to identity.
The perception of host in the above method characterizes：Face picture, fingerprint, person's handwriting, sound, iris, eyeprint, palm vein
The one of which such as line, appearance or multinomial attributive character, i.e. perception characterization are the intrinsic a variety of marker characteristics of host.
The perception characterization bottom of comparison host in the above method and the perception characterization source of host obtain qualification result and include：Root
The perception characterization source that the perception characterization bottom and host that compare host are matched according to representation pattern recognizer obtains qualification result, wherein
Representation pattern recognizer includes the one of which or more such as deep learning algorithm, machine learning algorithm, mathematical feature model algorithm
.
Above-mentioned representation pattern recognizer matching compares the perception characterization bottom of host and the perception characterization source of host
The face of host is compared as the perception of host characterizes to obtain qualification result, is compared according to fingerprint matching algorithm according to face recognition algorithm
The fingerprint host of host perception characterization obtain qualification result, according to voiceprint recognition algorithm compare host sound host perception
Characterization obtains qualification result, characterizes to obtain qualification result etc. according to the perception of the iris host of Algorithm of Iris Recognition comparison host.
The face of host is compared as the perception of host characterizes to obtain qualification result according to face recognition algorithm in the above method
Further comprise：The feature vector that face picture is obtained according to convolutional neural networks deep learning algorithm for pattern recognition, calculates host's
The Euclidean distance of the feature vector of perception characterization bottom face picture and the feature vector of the perception characterization source face picture of host, works as Euclidean distance
Less than specified threshold then host perception characterization bottom face picture and host perception characterization source face picture belong to same host then identify at
Work(, otherwise identification failure or the feature vector according to mathematical feature model algorithm acquisition face picture, are sentenced by classification or aggregating algorithm
The perception characterization bottom face picture of disconnected host and host perception characterization source face seems no to belong to same host.
The result of output identification success or failure in the above method is concretely：The perception for comparing host characterizes successfully then
Judge that the identity of host is effective, identifies successfully；The perception characterization failure for comparing host then judges the identity mark of host
Knowledge is invalid, identification failure.The result of output identification success or failure includes showing to identify successfully on user interface
Or the information and/or record of failure identify the result of success or failure.
The embodiment of the present invention additionally provides a kind of system of identification identity, including：Front-end application and background service journey
Sequence, wherein
Above-mentioned front-end application includes user interface section, Information reading unit, encryption unit, wherein
Above-mentioned user interface section is for receiving input information, the input information that distribution processor receives, output processing
As a result, it includes the information for receiving keyboard input, information, the information of touch screen input etc. of mouse input to receive input information.
Above-mentioned Information reading unit is used to read the identity ciphertext of host and reads the perception characterization source of host, packet
It includes and reads Quick Response Code or image, microphone reading sound etc. using photographic device.
The identity that above-mentioned encryption unit is used to encrypt host is ciphertext, including symmetric key algorithm is used to encrypt place
Main identity is identity ciphertext or the public key encryption host according to asymmetric key algorithm and preset digital certificate
Identity be ciphertext or calculate the identity of host according to hash algorithm to obtain abstract as identity be ciphertext.
Above-mentioned front-end application can also include pattern recognition unit, be used to compare the sense of host for comparing unit
Know that the perception characterization source of characterization bottom and host obtain qualification result.
Above-mentioned background service program includes Identification Service center cell, encryption/decryption element, pattern recognition unit, and data are deposited
Storage unit, wherein
Above-mentioned Identification Service center cell identifies identity application for accepting, the above-mentioned application of distribution processor, in response
The application treatment appraisal result stated, wherein
Above-mentioned encryption and decryption processing unit is used to decrypt the identity ciphertext of host using asymmetric key algorithm or make
The identity ciphertext of host is decrypted with symmetric key algorithm or the identity of host is encrypted using symmetric key algorithm；
Above-mentioned data storage cell includes the data such as identity, the perception of host characterization bottom for storing.
Above-mentioned pattern recognition unit is used to compare the perception characterization bottom of host and the perception characterization source of host and is identified
As a result.
The present invention provides a kind of sides of identification identity it can be seen from the technical solution that the embodiments of the present invention provide
Method and system are developed in existing mobile terminal, computer and communication interconnected network and dispose new application, make full use of existing wide
The general device used uses representation pattern recognizer and key algorithm rationally and effectively to solve to be made present in tradition card body
With inconvenient and privacy leakage, distinguish that difficulty such as leads to be falsely used at the security breaches.
Description of the drawings
Fig. 1 is the implementation illustration of the system application environment and function of the present invention；
Fig. 2 is the implementation illustration of the identification identity general step of the present invention.
Specific implementation mode
Embodiments of the present invention are described in detail and are illustrated below in conjunction with the accompanying drawings.
First, the system for introducing identification identity is the application environment and function module of the present invention, please refers to attached drawing 1.
The system of the identification identity of the present invention includes front-end application (Application, abbreviation APP) and background service
Program (abbreviation background system), front-end A PP host include mobile phone or personal computer etc., and background system host includes computer clothes
Business device or personal computer etc..Front-end A PP includes at least 1001 user interface sections, 1002 Information reading units, 1003 encryptions
Unit, front-end A PP can further include 1004 pattern recognition units.Background system include 1010 Identification Service center cells,
1011 encryption/decryption elements, 1012 pattern recognition units, 1013 data storage cells, pattern recognition unit can regard specific implementation position
In front-end A PP and/or background system.The general integration realizations of front-end A PP in one, specific implementation program be mobile terminal APP or
The web page program run on computer program or browser software.Background system is the ASC administrative service center of system, each function
Unit can individually or integration realization deployment, specific implementation program be internet site background system or application server programs or
Database program.1013 general individually deployment, are implemented as database or data in magnetic disk file.Front-end A PP and background system
It is generally connected by communication networks such as internets, is communicated using communication protocol, such as：Hypertext transfer protocol
Hypertext transfer protocol channel (the Hyper Text of (Hypertext transfer protocol, abbreviation HTTP) or safety
Transfer Protocol over Secure Socket Layer, abbreviation HTTPS) etc..Background system or front-end A PP functions
Native operating sys-tern calling interface or transmission control protocol/Internet Protocol are used according to actual deployment between unit
Agreements such as (Transmission Control Protocol/Internet Protocol, abbreviation TCP/IP) carry out communication link
It connects.Divide the work between front-end A PP and background system and each functional unit and coordinate, constitutes the basic operation of present system
System and environment.
Unit 1001 are responsible for receiving input information, the input information that distribution processor receives, output handling result.It receives defeated
It includes receiving user's input information, network interface input information to enter information, and network interface input information includes the sound that backstage is sent
Answer or detect message.User's input information includes identification application, identity encryption application etc..The identification that distribution processor receives
Application includes：Check up and appraisal application input information, structure identification application communication protocol message, filling identification application are input information to
The message sends the message etc..The specific implementation of user's input information includes by Optical devices input Quick Response Code, by with bluetooth
(Bluetooth) or WLAN (WIFI) connects the information read, passes through global positioning system (Global Position
System, abbreviation GPS) read information, the information of keyboard input, the information read by mobile network, read by microphone
The information etc. taken.
Unit 1002 be used for read host identity ciphertext and/or read host perception characterization source, using including
Quick Response Code is read in the scanning of the Optical devices such as camera, electronics barcode scanning gun, and translation Quick Response Code obtains the identity ciphertext of host；Make
It with the face picture of the Optical devices such as camera intake host or listens to the sound of host using audio units such as microphones or use refers to
Line device obtains the fingerprint of host or using one of which or more such as the iris of the Optical devices such as camera intake host or eyeprints
.
The identity that Unit 1003 encrypt host is ciphertext, including uses the identity mark of symmetric key algorithm encryption host
Know the identity for identity ciphertext or the public key encryption host according to asymmetric key algorithm and preset digital certificate
It is ciphertext for ciphertext or to obtain digital digest as identity according to the identity of hash algorithm calculating host.Above-mentioned is non-
Symmetric key algorithm includes but not limited to Luo Enandilaien (Ron Rivest, Adi Shamir, Len Adleman, abbreviation
RSA) algorithm, elliptic curve cipher (Elliptic Curves Cryptography, abbreviation ECC) algorithm (such as：Ecc25519
Algorithm), Digital Signature Algorithm (Digital Signature Algorithm, abbreviation DSA), hash algorithm includes but not limited to
Eap-message digest (Message Digest, abbreviation MD), Secure Hash Algorithm (Secure Hash Algorithm, abbreviation SHA) are calculated
Method.Unit 1003 can be according to the digital certificate with regard to the preset asymmetric key algorithm comprising public key when being embodied in deployment.
Unit 1004 are used to match or compare the perception characterization bottom of host and the perception characterization source of host and obtain qualification result.
The representation pattern recognizer that the perception characterization source at the perception characterization bottom and host that compare host uses, representation pattern recognizer
It can specifically include image recognition algorithm, characteristic mathematical model algorithm, voice recognition algorithm etc..Algorithm for pattern recognition includes but not
It is limited to the combination of deep learning algorithm, machine learning algorithm, feature extraction algorithm, feature extraction algorithm and machine learning algorithm
Deng deep learning algorithm includes convolutional neural networks (CNN) etc., and machine learning algorithm includes support vector machines (Support
Vector Machine, abbreviation SVM), Iterative classification algorithm (AdaBoost) etc., feature extraction algorithm further includes that direction gradient is straight
Side's figure (Histogram of Oriented Gradient, abbreviation HOG) characteristics algorithm, local binary patterns (Local
Binary Pattern：Abbreviation LBP), feature templates (Haar) algorithm, the method for geometric properties, Local Features Analysis method
(Local Face Analysis, abbreviation LFA), eigenface method (Eigen-face).Characteristic mathematical model algorithm includes hidden horse
Er Kefu model methods (Hidden Markov Model, abbreviation HMM), gauss hybrid models (GMM) algorithm etc..Such as：According to
Convolutional neural networks deep learning algorithm obtains the multidimensional characteristic vectors of face picture, calculates the multidimensional of the perception characterization bottom face picture of host
The Euclidean distance of the multidimensional characteristic vectors of the perception characterization source face picture of feature vector and host, when Euclidean distance is less than specified threshold
Then the perception characterization bottom face picture of host and the perception characterization source face picture of host belong to same host and then identify success, and otherwise identification is lost
It loses.
For accepting the application of identification identity, identity encryption application etc., the above-mentioned application of distribution processor is rung Unit 1010
Answer above-mentioned application handling result.It includes the solicitation message that receiving front-end APP is sent to accept application, parses solicitation message, is extracted
Application information.The above-mentioned application of distribution processor includes calling correlation unit to carry out subsequent processing according to applying type.
Unit 1012 are for encryption or decryption identity mark.Encryption or decryption specific implementation can use symmetric key algorithm
Or asymmetric key algorithm is realized.Symmetric key algorithm includes but not limited to Advanced Encryption Standard (Advanced Encryption
Standard, abbreviation AES), Lee Vista code (Rivest Code, abbreviation RC) algorithm, fork look into (Chacha) algorithm etc..Identity
Mark generally comprises one or more combinations such as identification number, passport number, tissue code, vehicle motor number, name.
Unit 1013 are used to compare the perception characterization of host with Unit 1004 for use pattern recognizer comparing unit
The perception characterization source of bottom and host obtain qualification result.Pattern-recognition refers to the various forms of (numbers to characterization things or phenomenon
It is value, word and logical relation) information handled and analyzed, to be described, recognize to things or phenomenon, classify and
The process of explanation.Such as：The content of sound is identified according to neural network deep learning algorithm and obtains the vocal print feature of sound
Vectorial source, first compares whether the content identified matches, if content matching, compares the vocal print feature vector source for obtaining sound
Whether matched with the vocal print feature vector bottom of host, identified if matching and successfully (be recognized as same host), otherwise identification is lost
It loses.
It includes the data such as identity, the perception of host characterization bottom that Unit 1017, which are mainly used for storage,.Data storage cell
Specific implementation can be database program or customized data file, and user information is stored in database by the form of table
In or file in, such as data storage cell be embodied as the inscriptions on bones or tortoise shells (Oracle) or my structured query language (MySQL) number
According to library, user information is inquired or updated by structured query language (Structured Query Language, abbreviation SQL).
By above-mentioned identity authentication system, when hiding identity private information, identification body can be effectively facilitated
Part.
Operating procedure of the present invention and relevant operation is described in detail below by embodiment, in combination with upper plane system.
Attached drawing 2 describes the embodiment of identification identity general step, specifically includes：
Step S2001, crypto identity mark, that is, the identity for encrypting host are identity ciphertext.Identity packet
The one of which or multinomial such as title, licence number are included but are not limited to, title includes organization name, name etc., and licence number includes
Identification number, passport number, organization mechanism code, vehicle motor number, license plate number etc..Host can be with natural person, organization
Equal members of society, can also be vehicle, house property and other items.Crypto identity mark, which implements, may include：Use such as AES etc. pairs
The identity that key algorithm encrypts host is referred to as identity ciphertext；The identity mark of host is encrypted using asymmetric key algorithm
It is identity ciphertext to know；The digital digest value that the identity of host is calculated using hash algorithm is referred to as identity ciphertext.
Crypto identity mark can also pass through 1011 cell processings of backstage in 1003 cell processings of APP.When 1003 cell processing
For processing locality, backstage, backstage are arrived by needing front-end A PP to send crypto identity mark application when 1011 cell processing of backstage
After Unit 1010 receive crypto identity mark solicitation message, message is parsed, after calling 1011 cell processings, includes in return
Unit 1003 of the message of identity ciphertext to front-end A PP.
Step S2002 reads identity, that is, reads the identity ciphertext of host.Specific implementation may include：It reads
Quick Response Code identity ciphertext reads keyboard input identity ciphertext, passes through optical character identification (Optical
Character Recognition, abbreviation OCR) technology reads identity ciphertext, reads the identity transmitted by bluetooth
Ciphertext.Such as：The Quick Response Code for including identity ciphertext is read using including the scanning of the Optical devices such as camera, electronics barcode scanning gun
Picture, translation Quick Response Code obtain the identity ciphertext of host.Such as：Unit 1002 open camera, are read by camera
Include the two-dimension code image of identity ciphertext, place is then obtained according to Quick Response Code coding standard or rule translation two-dimension code image
Main identity ciphertext.
Step S2003, reads the perception characterization source of host, that is, the perception for reading host characterizes source.Specific implementation can wrap
It includes：The face picture of host is absorbed using Optical devices such as cameras or is listened to the sound of host using audio units such as microphones or is made
The fingerprint of host is obtained with fingerprint device or using one of which such as the iris of the Optical devices such as camera intake host or eyeprints
Or it is multinomial.Such as：Unit 1002 open camera, and the face picture processing that host is absorbed by camera is image graphic.This step
After there is no stringent sequencing requirement, step S2002 that can be located at this step with step S2002.
Step S2004, decryption identity mark, that is, decrypt the identity ciphertext of host.This step is optional step, works as place
This step need not do any processing when main identity ciphertext is digital digest.The identity ciphertext for decrypting host is specific
Realization includes：The identity ciphertext of host is decrypted using symmetric key algorithm or decrypts host's using asymmetric key algorithm
Identity ciphertext, such as：The identity of host is decrypted by private key using asymmetric key algorithm Curve2559 or RSA
Ciphertext obtains the identity of plaintext.Unit 1011 are responsible for decrypting the identity ciphertext of host, and Unit 1010 are by place to be decrypted
Main identity ciphertext gives Unit 1011, and the identity ciphertext of the decryption host of Unit 1011 obtains the identity mark of host
Know, the identity of host is then returned into Unit 1010.
Step S2005 extracts the perception characterization bottom of host, i.e., extracts host according to the ciphertext of identity or identity
Perception characterize bottom.Host perception characterization bottom refer to host put on record in advance the host to keep on file perception characterization.When the identity of host
When mark ciphertext is digital digest, the perception that host is directly extracted according to identity digital digest characterizes bottom.Specific implementation packet
It includes：According to the digital digest ciphertext of identity or identity from background data base extract host perception characterization bottom or according to
Identity is extracted the perception characterization bottom of host from host's identity remote service center or is carried from local file according to identity
The perception of host is taken to characterize bottom.Such as：Unit 1010 are by http protocol messages according to the name of host and identification number from body
The name of host and identification number are encapsulated as http and disappeared by the identification photographs of part information service center extraction host, Unit 1010
Breath, then sends the message to identity information service centre, and identity information service centre is according to the name and identification number of host
The face of host is found as photo, photo is returned into Unit 1010 by http response messages.
Step S2006 compares the perception characterization of host, that is, representation pattern recognizer is used to match or compare the sense of host
Know that the perception characterization source of characterization bottom and host obtain qualification result.The perception of host characterizes：Face picture, fingerprint, the pen of host
The one of which such as mark, sound, iris, eyeprint, palm vein line, appearance or multinomial attribute or feature, the perception of host, which characterizes, is
The intrinsic appreciable identification marker characteristic of host.It is identified in the perception characterization source at the perception characterization bottom and host that compare host
As a result include：The perception characterization source that the perception characterization bottom and host that compare host are matched according to representation pattern recognizer is reflected
It is fixed as a result, wherein representation pattern recognizer include deep learning algorithm, machine learning algorithm, mathematical feature model algorithm etc. its
In it is one or more.Such as：The face of host is compared as the perception of host characterizes to obtain qualification result, root according to face recognition algorithms
The perception that the fingerprint host of host is compared according to fingerprint matching algorithm characterizes to obtain qualification result, compares place according to voiceprint recognition algorithm
Main sound host perception characterization obtain qualification result, according to Algorithm of Iris Recognition compare host iris host perception table
Obtain qualification result etc..The pattern recognition unit for executing representation pattern recognizer can be positioned at backstage Unit 1012 or preceding
Hold Unit 1004.Such as：HOG mathematical feature model methods be exactly by a face as image elder generation gray processing processing, using gamma
(Gamma) correction method calculates the gradient of each pixel of image to face as the standardization (normalization) of image progress color space, will
Image is divided into cellule unit (cells), counts the histogram of gradients of each cell and can form description of each cell
(descriptor), a block (block) will be formed per several cell, the feature of all cell in a block
Descriptor is together in series and just obtains the HOG feature descriptor of the block, the HOG features of all block in image
Descriptor is together in series to obtain the HOG feature descriptor of the image, the HOG features descriptor inputs point of image
Class device Adaboost is detected judgement classification.The cascade classifier Adaboost that image compares is that a positive negative sample of use is pre-
First trained similarity grader, advance trained grader can divide the HOG features descriptor of image automatically
Class judges, i.e., inputs the HOG features descriptor and perception characterization source HOG features at the perception characterization bottom of host respectively
Descriptor judges whether same category (or similarity is close).Compare the perception table at perception the characterization bottom and host of host
The qualification result that sign source obtains includes identifying successfully or identifying failure.
Step S2007, the result of output identification success or failure.Concretely：The perception for comparing host characterizes successfully then
Judge that the identity of host is effective, identifies successfully；The perception characterization failure for comparing host then judges the identity mark of host
Knowledge is invalid, identification failure.The result of output identification success or failure includes showing to identify successfully on user interface
Or the information and/or record of failure identify the result of success or failure.
By above-mentioned identity identifying method, when hiding identity private information, identification body can be effectively facilitated
Part, solve the problems such as identity is falsely used.
The embodiment of identification identity step using public key encryption identity is described below, specific implementation includes：
Step S2011, the identity that host is encrypted using asymmetric key algorithm are identity ciphertext.APP's
Unit 1003 are disclosed close using RSA or elliptic curve asymmetric key algorithm using the identity of public key encryption host
Key can be built in advance in Unit 1003 of APP.
Step S2012 reads the identity ciphertext of host.Such as：It is defeated using the optics such as camera or electronics barcode scanning gun
Enter device and reads identity ciphertext Quick Response Code.Unit 1002 open cam device, input image in 2 D code, translate Quick Response Code
Image obtains identity ciphertext, and translation Quick Response Code specifically includes：It finds detection figure and obtains locating piece and positioning pattern, determine
The coordinate of module in two-dimensional code symbol, gray processing 2 D code information pixel remove the noise of 2 D code information pixel, binaryzation two
Dimension code information pixels obtain binary message, by obtained binary message into obtaining the letter of Quick Response Code after row decoding and error correction
Breath.
Step S2013 reads the face image of host.Specific implementation may include：Unit 1002 open camera, pass through
The face picture processing that camera absorbs host is image graphic.
Step S2014 decrypts the identity ciphertext of host.Specific implementation includes：Unit 1011 use unsymmetrical key
The identity ciphertext that algorithm elliptic curve asymmetric key algorithm or RSA decrypt host by private key obtains the identity mark of plaintext
Know.
Step S2015 extracts the face image bottom of host according to identity.Such as：Unit 1010 are by the name of host
Http protocol messages are packaged into identification number, identity information service centre are then sent the message to, in identity information service
The heart receives the facial photo image for finding the host that keeps on file and (put on record) after http protocol messages according to the name and identification number of host,
Photograph image is returned into Unit 1010 by http response messages.
Step S2016, the face image that host is compared using convolutional neural networks deep learning algorithm for pattern recognition are obtained
Qualification result.Face image is inputted convolutional neural networks acquisition by the prefabricated trained convolutional neural networks of Unit 1012 respectively
The X dimensional feature vectors of face picture calculate the Euclidean distance of two X dimensional feature vectors, when Euclidean distance is then identified less than specified threshold
Success, otherwise identification failure.The face image bottom of host can be X dimensional feature vectors, can be omitted input face image at this time
Bottom is to neural network.
Step S2017, the result of output identification success or failure.
By above-mentioned identity identifying method, convolutional neural networks deep learning algorithm for pattern recognition technology and non-right is used
Claim password encryption decryption technology, can effectively facilitate identification identity, solve the problems such as identity is falsely used.
The embodiment of identification identity step using symmetric key encryption identity, specific implementation packet are described below
It includes：
Step S2021, the identity that host is encrypted using symmetric key algorithm are identity ciphertext.The 1001 of APP
The identity of host is packaged into encryption application http protocol messages by unit, sends the message to background service center, backstage
Unit 1010 receive encryption solicitation message, and 1010 cell call Unit 1011 is encrypted, then passes through identity
Http response messages return to Unit 1001.
Step S2022 reads the identity ciphertext of host.
Step S2023 reads the sound of host.Specific implementation may include：Unit 1002 open microphone, listen to host
Sound.
Step S2024 decrypts the identity ciphertext of host.Specific implementation includes：Unit 1011 are calculated using symmetric key
The identity ciphertext of method (AES) decryption host obtains the identity of plaintext.
Step S2025 extracts the sound of keeping on file of host according to identity (i.e. sound characterizes bottom).Such as：Unit 1010
Extract the sound of keeping on file of host from Unit 1013 using sql like language using the name and identification number of host.
Step S2026 is characterized using the sound of neural network deep learning algorithm for pattern recognition comparison host and is identified
As a result.Sound is inputted the similarity that neural network obtains sound by Unit 1012 respectively using advance trained neural network,
When sound similarity then identifies success more than specified threshold, otherwise identification fails.
Step S2027, the result of output identification success or failure.
By above-mentioned identity identifying method, vocal print algorithm for pattern recognition and symmetric cryptographic algorithm encrypting and decrypting skill are used
Art can effectively facilitate identification identity, solve the problems such as identity is falsely used.
The preferable specific implementation mode of the above, the only embodiment of the present invention, but the protection domain of the embodiment of the present invention
It is not limited thereto, any one skilled in the art, can be light in the technical scope that the embodiment of the present invention discloses
The change or replacement being readily conceivable that should all be covered within the protection domain of the embodiment of the present invention.Therefore, the guarantor of the embodiment of the present invention
Shield range should be subject to the protection scope in claims.
Claims (10)
1. a kind of method of identification identity, which is characterized in that including：
The identity ciphertext of host is read,
The perception for reading host characterizes source,
The perception that host is extracted according to identity characterizes bottom,
The perception characterization source at the perception characterization bottom and host that compare host obtains qualification result.
2. according to the method described in claim 1, it is characterized in that, the identity ciphertext of the reading host further may be used
To include：
Quick Response Code is read using being scanned including Optical devices such as camera, electronics barcode scanning guns, translation Quick Response Code obtains the body of host
Part mark ciphertext.
3. according to the method described in claim 1, it is characterized in that, the perception characterization source of the reading host may further
Including：
Using the Optical devices such as camera absorb host face picture or
Using the audio units such as microphone listen to host sound or
Using fingerprint device obtain host fingerprint or
The one of which such as iris or the eyeprint of host or multinomial are absorbed using Optical devices such as cameras.
4. according to the method described in claim 1, it is characterized in that, the perception for extracting host according to identity characterizes
It can further include before bottom：The identity ciphertext for decrypting host, including：
Using symmetric key algorithm decrypt host identity ciphertext or
The identity ciphertext of host is decrypted using asymmetric key algorithm.
5. according to the method described in claim 1, it is characterized in that, the perception characterization of the host includes：
The one of which such as the face picture of host, fingerprint, person's handwriting, sound, iris, eyeprint, palm vein line, appearance or multinomial attribute are special
Sign.
6. according to the method described in claim 1, it is characterized in that, the sense at perception the characterization bottom and host of the comparison host
Know that characterization source obtains qualification result and includes：
The perception characterization source that the perception characterization bottom and host that compare host are matched according to representation pattern recognizer obtains identification knot
Fruit, wherein
Representation pattern recognizer includes but not limited to deep learning algorithm, machine learning algorithm, mathematical feature model algorithm etc.
One of which is multinomial.
7. according to the method described in claim 1,5,6, which is characterized in that the perception characterization bottom of the comparison host and host
Perception characterization source obtain qualification result and further comprise：
According to convolutional neural networks deep learning algorithm obtain face picture feature vector, calculate host perception characterize bottom face as
The Euclidean distance of the feature vector of the perception characterization source face picture of feature vector and host, when Euclidean distance is less than specified threshold then place
The perception characterization source face picture of main perception characterization bottom face picture and host belongs to same host and then identifies success, otherwise identification failure.
8. according to the method described in claim 1,5,6, which is characterized in that the perception characterization bottom of the comparison host and host
Perception characterization source obtain qualification result and further comprise：
The feature vector that face picture is obtained according to mathematical feature model algorithm judges the perception table of host by classification or aggregating algorithm
Whether the feature vector for levying the feature vector of bottom face picture and the perception characterization source face picture of host belongs to same host.
9. according to the method described in claim 1, it is characterized in that, the sense at perception the characterization bottom and host of the comparison host
Know that characterization source obtains including further after qualification result：
The result of output identification success or failure.
10. according to the method described in claim 1, it is characterized in that, the advance of the identity ciphertext of the reading host
One step can also include：
Using symmetric key algorithm encrypt host identity be identity ciphertext or
Using asymmetric key algorithm encrypt host identity be identity ciphertext or
The digital digest value that the identity of host is calculated using hash algorithm is identity ciphertext.
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