CN117494092A - Scenic spot ticket non-inductive verification method, system and medium based on living organism identification - Google Patents

Scenic spot ticket non-inductive verification method, system and medium based on living organism identification Download PDF

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Publication number
CN117494092A
CN117494092A CN202311516872.9A CN202311516872A CN117494092A CN 117494092 A CN117494092 A CN 117494092A CN 202311516872 A CN202311516872 A CN 202311516872A CN 117494092 A CN117494092 A CN 117494092A
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authentication
target
biological
multidimensional
verification
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Inventor
于智军
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Shenzhen Ce Software Co ltd
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Shenzhen Ce Software Co ltd
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Priority to CN202311516872.9A priority Critical patent/CN117494092A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • 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
    • G06V40/16—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
    • 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
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G07C9/30—Individual registration on entry or exit not involving the use of a pass
    • G07C9/32—Individual registration on entry or exit not involving the use of a pass in combination with an identity check
    • G07C9/37—Individual registration on entry or exit not involving the use of a pass in combination with an identity check using biometric data, e.g. fingerprints, iris scans or voice recognition

Abstract

The invention relates to the technical field of biological recognition, and discloses a scenic spot ticket noninductive verification method, a scenic spot ticket noninductive verification system and a scenic spot ticket noninductive verification medium based on biological living body recognition, wherein the scenic spot ticket noninductive verification method comprises the following steps of: extracting multidimensional biological characteristics according to basic attributes of a target user, and encrypting the multidimensional biological characteristics; synchronously storing the encrypted multidimensional biological characteristics into a personal account, and synchronously updating and transmitting the multidimensional biological characteristics to a biological identification authentication device; determining target authentication equipment according to a storage path of real-time video data of a target tourist, and extracting target multidimensional biological characteristics of the target tourist in the real-time video data; calculating an authentication permission value of the target multi-dimensional biological feature and the multi-dimensional encrypted biological feature, and generating an authentication information matrix according to the authentication permission value; calculating ticket verification values according to the authentication information matrix, and updating the authentication information matrix; and when the ticket verification value is greater than or equal to the verification threshold value, generating a ticket verification license of the target tourist. The invention can improve the efficiency of the non-inductive verification of scenic spot tickets.

Description

Scenic spot ticket non-inductive verification method, system and medium based on living organism identification
Technical Field
The invention relates to the technical field of biological identification, in particular to a scenic spot ticket noninductive verification method, a scenic spot ticket noninductive verification system and a scenic spot ticket noninductive verification medium based on biological living body identification.
Background
With the improvement of the spirit pursuit of people, scenic spots for holding large-scale activities, such as theme parks and music festival, the verification of scenic spot tickets can be a test, so in order to improve the speed of the scenic spot ticket verification, the verification or the number of authentication equipment terminals of the scenic spot tickets need to be analyzed, and the efficiency of the scenic spot ticket non-sensing verification is improved.
The conventional scenic spot ticket checking technology is mainly used for checking tickets in an authentication device based on the facial features of target tourists. In practical application, verification may be inaccurate only through facial features of the tourist, or verification is performed in one authentication device, so that waiting time of the tourist is increased, and verification speed of scenic spot tickets of the tourist is slower, so that efficiency of non-inductive verification of scenic spot tickets is lower.
Disclosure of Invention
The invention provides a scenic spot ticket non-inductive verification method, a scenic spot ticket non-inductive verification system and a scenic spot ticket non-inductive verification medium based on living organism identification, which mainly aim to solve the problem of low efficiency in scenic spot ticket non-inductive verification.
In order to achieve the above object, the present invention provides a scenic spot ticket noninductive verification method based on living organism identification, comprising:
s1, acquiring basic attributes of a target user, extracting multidimensional biological characteristics of the target user according to the basic attributes, and encrypting the multidimensional biological characteristics by using a preset double encryption algorithm to obtain multidimensional encrypted biological characteristics;
s2, synchronously storing the multidimensional encryption biological characteristics into a pre-built personal account, and synchronously updating the multidimensional encryption biological characteristics in the personal account and sending the multidimensional encryption biological characteristics to preset biological identification authentication equipment;
s3, acquiring real-time video data of a target tourist, determining target authentication equipment in the biological recognition authentication equipment according to a storage path of the real-time video data, and extracting target multidimensional biological characteristics of the target tourist in the real-time video data;
s4, calculating an authentication permission value between the target multi-dimensional biological feature and the multi-dimensional encrypted biological feature in the target authentication equipment by using a preset two-way authentication algorithm, and generating an authentication information matrix of the target tourist according to the authentication permission value, wherein the calculating of the authentication permission value between the target multi-dimensional biological feature and the multi-dimensional encrypted biological feature in the target authentication equipment by using the preset two-way authentication algorithm comprises the following steps:
Decrypting the multi-dimensional encrypted biometric to obtain a multi-dimensional authenticated biometric;
calculating an authentication grant value between the target multi-dimensional biometric and the multi-dimensional authentication biometric using a two-way authentication algorithm as follows:
wherein Q is the authentication grant value, alpha k For the kth dimension feature value, beta, in the target multidimensional biological feature k For the k-th dimension characteristic value in the multidimensional authentication biological characteristic, h is a forward feedback factor, g is a reverse feedback factor, and m is a characteristic dimension;
s5, calculating ticket verification values of the target tourists according to the authentication information matrix through a preset dissimilating algorithm, and updating the authentication information matrix when the ticket verification values are smaller than a preset verification threshold value until the ticket verification values are larger than or equal to the preset verification threshold value;
and S6, when the ticket verification value is greater than or equal to a preset verification threshold value, generating a ticket verification license of the target tourist.
Optionally, the extracting the multidimensional biometric of the target user according to the basic attribute includes:
extracting the unique identity of the target user from the basic attribute;
collecting the face information characteristics and fingerprint information characteristics of the target user according to the unique identity;
And carrying out feature fusion on the face information features and the fingerprint information features to obtain the multidimensional biological features of the target user.
Optionally, the encrypting the multidimensional biological feature by using a preset double encryption algorithm to obtain a multidimensional encrypted biological feature includes:
performing feature coding on the multidimensional biological feature to obtain a multidimensional biological coding feature;
generating a hidden encryption key according to the multidimensional biological coding characteristics and a preset target sequence;
generating a ciphertext encryption information factor according to the hidden encryption key and the target sequence;
encrypting the multidimensional biological feature according to the hidden encryption key and the ciphertext encryption information factor by using a double encryption algorithm as follows to obtain the multidimensional encrypted biological feature:
wherein P is the multi-dimensional encrypted biometric, A is the multi-dimensional biometric, delta is the hidden encryption key,is the exclusive or operation sign, q is the sign factor, r 2 And encrypting a second target sequence in the information factor for the ciphertext, wherein omega is an information encryption embedded vector.
Optionally, the sending the multi-dimensional encrypted biometric synchronous update in the personal account to a preset biometric authentication device includes:
Generating a bidirectional authentication contract between the biometric authentication device and the personal account according to the authentication device identifier of the biometric authentication device;
constructing a bidirectional authentication security channel between the biometric authentication device and the personal account according to the bidirectional authentication contract;
extracting a bidirectional authentication update certificate of the bidirectional authentication contract according to a preset timestamp;
and synchronously updating the multidimensional encrypted biological characteristics through the bidirectional authentication security channel and the bidirectional authentication updating certificate and sending the multidimensional encrypted biological characteristics to the biological identification authentication equipment.
Optionally, the determining a target authentication device in the biometric authentication device according to the storage path of the real-time video data includes:
generating an authentication storage matrix by an authentication device identifier of the biometric authentication device and a storage path of the biometric authentication device;
carrying out path analysis on the storage path of the real-time video data to obtain a path analysis identifier;
matching the path analysis identifier with the identifier storage mapping relation in the authentication storage matrix to obtain a matching logic value;
and when the matching logic value is equal to a preset target matching threshold value, determining target authentication equipment in the biological identification authentication equipment.
Optionally, the extracting the target multidimensional biometric of the target guest in the real-time video data includes:
extracting video frame data of the real-time video data;
performing semantic segmentation on the video frame data to obtain pixel semantic categories of the video frame data;
determining an eye pixel optical flow vector of the video frame data according to the pixel semantic category;
calculating a dynamic value of the real-time video data according to the eye pixel optical flow vector, wherein the dynamic value calculation formula is as follows:
wherein T is the dynamic value,b is the semantic weight of the eye pixels, x is the pixel abscissa, y is the pixel ordinate,l is the brightness of the eye pixels, V is the eye pixel optical flow vector, t i N is the frame length of the video frame data;
when the dynamic value is equal to a preset target dynamic threshold value, collecting target face information characteristics and target fingerprint information characteristics of the target tourists;
and carrying out feature fusion on the target face information features and the target fingerprint information features to obtain target multidimensional biological features of the target tourists.
Optionally, the generating the authentication information matrix of the target tourist according to the authentication permission value includes:
Extracting the authentication information of the target tourist according to the authentication permission value;
determining the authentication authority information of the target tourist according to the authentication information;
and generating an authentication information matrix of the target tourist according to the authentication authority information and the authentication permission value.
Optionally, the calculating, by a preset dissimilating algorithm, the ticket verification value of the target tourist according to the authentication information matrix includes:
determining an authentication influence factor of the scenic spot ticket verification according to the authentication information matrix;
determining an authentication permission weight corresponding to the authentication permission value in the authentication information matrix according to the authentication influence factor;
calculating ticket verification values of the target tourists according to the authentication permission weights and the authentication permission values through the following dissimilating algorithm:
wherein M is the ticketVerification value, lambda is the control factor of the external factor, gamma e For verification of extrinsic factors, delta d Authentication permission weight for the d-th authentication device, H d The authentication permission value for the D-th authentication device, E is the number of factors of the extrinsic factors, and D is the number of authentication devices.
In order to solve the above problems, the present invention also provides a scenic spot ticket non-inductive verification system based on living organism identification, the system comprising:
The multi-dimensional biological feature encryption module is used for acquiring basic attributes of a target user, extracting multi-dimensional biological features of the target user according to the basic attributes, and encrypting the multi-dimensional biological features by using a preset double encryption algorithm to obtain multi-dimensional encrypted biological features;
the multi-dimensional encryption biological feature transmitting module is used for synchronously storing the multi-dimensional encryption biological features into a pre-built personal account and synchronously updating the multi-dimensional encryption biological features in the personal account and transmitting the multi-dimensional encryption biological features into a pre-set biological identification authentication device;
the target multidimensional biological feature extraction module is used for acquiring real-time video data of a target tourist, determining target authentication equipment in the biological recognition authentication equipment according to a storage path of the real-time video data, and extracting target multidimensional biological features of the target tourist in the real-time video data;
the authentication information matrix generation module is used for calculating an authentication permission value between the target multidimensional biological feature and the multidimensional encryption biological feature in the target authentication equipment by using a preset bidirectional authentication algorithm, and generating an authentication information matrix of the target tourist according to the authentication permission value;
The ticket checking value calculating module is used for calculating ticket checking values of the target tourists according to the authentication information matrix through a preset dissimilating algorithm, and updating the authentication information matrix until the ticket checking values are larger than or equal to a preset checking threshold when the ticket checking values are smaller than the preset checking threshold;
and the ticket checking license generation module is used for generating the ticket checking license of the target tourist when the ticket checking value is greater than or equal to a preset checking threshold value.
In order to solve the above-mentioned problems, the present invention also provides a medium in which at least one computer program is stored, the at least one computer program being executed by a processor in an electronic device to implement the above-mentioned scenic spot ticket non-inductive verification method based on living organism identification.
According to the embodiment of the invention, the multidimensional biological characteristics of the target user are extracted, so that the multidimensional biological characteristics are encrypted, and the safety of multidimensional biological characteristic storage is improved; synchronously storing the multidimensional encrypted biological characteristics into a pre-constructed personal account and synchronously updating and sending the multidimensional encrypted biological characteristics to biological identification authentication equipment, so that possible security threats and possible loopholes can be dealt with; the target authentication equipment is determined based on the real-time video data of the target tourist, and the target multidimensional biological characteristics of the target tourist are extracted, so that the authenticity of the target tourist can be ensured, and the accuracy of checking the scenic spot entrance ticket is improved; calculating an authentication permission value between the target vitamin characteristic and the multidimensional encryption biological characteristic in the target authentication equipment, generating an authentication information matrix of the target tourist according to the authentication permission value, and determining a verification value of a final cross-equipment verification scenic spot ticket of the target tourist so as to realize cross-equipment verification; calculating ticket verification values of the target tourists according to the authentication information matrix, and updating the authentication information matrix when the ticket verification values are smaller than verification threshold values, so that the accuracy of ticket verification of the target tourist attraction is improved; when the ticket verification value is greater than or equal to the verification threshold value, generating ticket verification license of the target tourist, and improving the speed of ticket verification in the scenic spot. Therefore, the scenic spot ticket non-inductive verification method, the scenic spot ticket non-inductive verification system and the scenic spot ticket non-inductive verification medium based on the living organism identification can solve the problem that the efficiency is lower when the scenic spot ticket non-inductive verification is carried out.
Drawings
FIG. 1 is a schematic flow chart of a scenic spot ticket non-inductive verification method based on living organism identification according to an embodiment of the invention;
FIG. 2 is a schematic flow chart of a method for synchronously transmitting multidimensional encrypted biometric according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of determining a target authentication device according to an embodiment of the present invention;
fig. 4 is a functional block diagram of a scenic spot ticket non-inductive verification system based on living organism identification according to an embodiment of the invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a scenic spot ticket non-inductive verification method based on biological living body identification. The execution subject of the scenic spot ticket non-inductive verification method based on the living organism identification comprises, but is not limited to, at least one of a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the application. In other words, the scenic spot ticket non-sensing verification method based on the living organism identification may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a scenic spot ticket non-inductive verification method based on living organism identification according to an embodiment of the invention is shown. In this embodiment, the scenic spot ticket non-inductive verification method based on living organism identification includes:
s1, acquiring basic attributes of a target user, extracting multidimensional biological characteristics of the target user according to the basic attributes, and encrypting the multidimensional biological characteristics by using a preset double encryption algorithm to obtain multidimensional encrypted biological characteristics.
In the embodiment of the present invention, the basic attribute refers to identification information of the target user, including name, age, gender, identification card number, etc. of the target user, where the basic attribute of the target user may be obtained from a pre-stored storage area by a computer sentence (such as a Java sentence, a Python sentence, etc.) with a data grabbing function, and the storage area includes, but is not limited to, a database. A blockchain.
Further, according to the basic attributes of the target users, the unique corresponding biological characteristics of each user can be extracted, more accurate identity verification can be provided for checking the scenic spot tickets of the target users, and the efficiency and accuracy of checking the tickets are improved.
In the embodiment of the invention, the multidimensional biological characteristics comprise the face characteristics and the fingerprint characteristics of the target user, or can comprise the sound characteristics and the iris characteristics of the target user.
In an embodiment of the present invention, the extracting the multidimensional biometric of the target user according to the basic attribute includes:
extracting the unique identity of the target user from the basic attribute;
collecting the face information characteristics and fingerprint information characteristics of the target user according to the unique identity;
and carrying out feature fusion on the face information features and the fingerprint information features to obtain the multidimensional biological features of the target user.
In detail, the unique identity identifier is an identifier of the target user, such as an identity card number can uniquely identify the identity information of the target user, the unique identity identifier of the target user in the basic attribute can be extracted through a computer sentence with a data capturing function, then the face information characteristic and the fingerprint information characteristic corresponding to the user are extracted based on the unique identity identifier of each target user, wherein the information such as the face feature point, the contour, the skin color and the like can be extracted through a face recognition algorithm, and the face recognition algorithm comprises but is not limited to a deep learning convolutional neural network algorithm; feature information such as lines, volumes, etc. in the fingerprint image may be extracted based on the fingerprint information features, wherein the fingerprint feature extraction algorithm includes, but is not limited to, a directional gradient histogram (Orientation Gradient Histogram) and a local binary pattern (Local Binary Pattern).
Specifically, the feature fusion is carried out on the face information features and the fingerprint information features, the multidimensional biological features of the target user can be obtained, the feature fusion can combine the information contained in different biological features to improve the accuracy and the robustness of recognition, the normalization processing can be carried out on the vectors of the face features and the vectors of the fingerprint features, the vectors can be ensured to have similar numerical ranges, so that the fusion can be carried out better, and the normalized face feature vectors and the fingerprint feature vectors are connected together according to a certain rule. The connection may be a simple splice, i.e. two vectors are connected in sequence into one longer vector; the method can also be weighted connection, namely, two vectors are respectively weighted and then connected, the connected long feature vectors are subjected to standardized treatment so as to ensure that the fused feature vectors have similar importance in each dimension, and if the dimension of the connected feature vectors is too high, principal Component Analysis (PCA) or other dimension reduction methods can be considered to be used for reducing the dimension to a proper dimension so as to reduce the calculation load and improve the recognition performance.
Further, the multi-dimensional biometric of the target user needs to be encrypted before being stored in a different biometric identification device, ensuring that the encryption of the biometric is more secure, thereby reducing the risk of unauthorized access or abuse of the biometric data.
In the embodiment of the invention, the multidimensional encryption biological feature refers to data obtained after the multidimensional biological feature is encrypted, so that the multidimensional biological feature is converted from plaintext to ciphertext and stored in the biological authentication and identification equipment in a ciphertext mode, and the storage safety of the multidimensional biological feature is ensured.
In the embodiment of the present invention, the encrypting the multidimensional biological feature by using a preset double encryption algorithm to obtain a multidimensional encrypted biological feature includes:
performing feature coding on the multidimensional biological feature to obtain a multidimensional biological coding feature;
generating a hidden encryption key according to the multidimensional biological coding characteristics and a preset target sequence;
generating a ciphertext encryption information factor according to the hidden encryption key and the target sequence;
encrypting the multidimensional biological feature according to the hidden encryption key and the ciphertext encryption information factor by using a double encryption algorithm as follows to obtain the multidimensional encrypted biological feature:
wherein P is the multi-dimensional encrypted biometric, A is the multi-dimensional biometric, delta is the hidden encryption key,is the exclusive or operation sign, q is the sign factor, r 2 And encrypting a second target sequence in the information factor for the ciphertext, wherein omega is an information encryption embedded vector.
In detail, converting the multidimensional biological characteristics into binary codes, so as to obtain the multidimensional biological coded characteristics after the binary codes, and further generating a hidden encryption key by the multidimensional biological coded characteristics and a random target sequence, namely performing exclusive-or operation according to the multidimensional biological coded characteristics and a first target sequence in the target sequence to obtain a first multidimensional exclusive-or sequence; performing exclusive-or operation on the multidimensional biological coding features and a second target sequence in the target sequences to obtain a second multidimensional exclusive-or sequence; performing exclusive-or operation on the first multidimensional exclusive-or sequence and the second exclusive-or sequence to obtain the hidden encryption key; the first target sequence and the second target sequence are binary sequences which are randomly generated, and the dimension of the binary sequences is the same as the dimension of the multidimensional biological coding feature, so that the hidden encryption key is obtained.
Specifically, the secret may be generated from the hidden encryption key and a second one of the target sequencesThe ciphertext encryption information factor is (delta, r) 2 ) And then, forming double encryption according to the hidden encryption key and the ciphertext encryption information factor together so as to improve the security of data encryption, and then encrypting the data of the multidimensional biological feature based on a double encryption algorithm, wherein an information encryption embedded vector omega in the double encryption algorithm is formed by encrypting vector elements one by one, or encrypting the whole vector, and protecting the multidimensional biological feature while maintaining vector semantic information; the sign factor q controls the positive and negative of the ciphertext encryption information factor, so that double encryption of the multidimensional biological characteristics can be realized, and the security of the multidimensional biological characteristic storage is improved.
Further, to realize cross-equipment verification of scenic spot tickets, the multidimensional biological characteristics of the user are required to be respectively stored in different biological identification and authentication equipment, so that verification efficiency of the scenic spot tickets is improved.
S2, synchronously storing the multidimensional encryption biological characteristics into a pre-built personal account, and synchronously updating the multidimensional encryption biological characteristics in the personal account and sending the multidimensional encryption biological characteristics to a preset biological identification authentication device.
In the embodiment of the invention, the personal account means that each target user has an account uniquely corresponding to the user, and the personal account is used for recording personal information of the user, such as user identity information, encryption keys, multidimensional biological characteristics, verification equipment and the like, so that the safety and the uniqueness of the user account can be ensured, wherein the multidimensional encrypted biological characteristics corresponding to each user can be synchronously stored in the personal account of each user through a preset account interface.
Further, the multi-dimensional biometric feature of the target user is stored in the personal account, so that cross-device verification can be achieved when the multi-dimensional biometric feature is verified, and the multi-dimensional biometric feature of the target user needs to be sent to different biometric authentication devices respectively.
In the embodiment of the invention, the biological recognition authentication equipment comprises but is not limited to fingerprint recognition equipment, face recognition equipment and mobile phone terminal equipment, and the biological recognition authentication equipment can acquire and compare the unique biological characteristics of the individual so as to ensure that only authorized users can access the protected resources.
In an embodiment of the present invention, referring to fig. 2, the step of sending the multi-dimensional encrypted biometric update in the personal account to a preset biometric authentication device includes:
s21, generating a bidirectional authentication contract between the biometric authentication device and the personal account according to the authentication device identifier of the biometric authentication device;
s22, constructing a bidirectional authentication security channel between the biometric authentication device and the personal account according to the bidirectional authentication contract;
s23, extracting a bidirectional authentication update certificate of the bidirectional authentication contract according to a preset time stamp;
s24, synchronously updating the multidimensional encryption biological characteristics through the bidirectional authentication security channel and the bidirectional authentication updating certificate, and sending the multidimensional encryption biological characteristics to the biological identification authentication equipment.
In detail, the biometric authentication device needs to provide its own unique identifier, which may be a digital certificate, a device serial number or other similar identifier, and the personal account receives and verifies the validity of the device identifier to ensure that the identity of the authentication device is legal and trusted, then a two-way authentication contract in the biometric authentication device and the personal account is constructed based on the authentication device identifier in the biometric authentication device, that is, the two-way authentication contract contains two address variables, which represent the addresses of the biometric authentication device and the personal account respectively, and two functions, one of which is used for authenticating the biometric authentication device and the other of which is used for authenticating the personal account, and when authenticating the biometric authentication device, only the biometric authentication device can call the function and mark it as authenticated; when authenticating a personal account, only the personal account may call the function and it is necessary to ensure that the biometric device has completed authentication first.
Specifically, a mutual authentication channel is established using a smart contract, and a mutual authentication process is automatically performed. When the authentication equipment and the personal account are communicated, the intelligent contract can automatically verify the identities of the two parties and ensure the safety of data transmission, and after the bidirectional authentication safety channel is established, the authentication equipment and the personal account system can mutually verify the identities of the other parties and ensure the legitimacy of the two parties of data transmission; acquiring a bidirectional authentication update certificate in the bidirectional authentication contract based on a preset time point, wherein the bidirectional authentication update certificate comprises addition or deletion of a personal account and a biological authentication device, such as adding a biological authentication device or deleting a biological authentication device; and synchronously updating the multidimensional encryption biological characteristics into the biological identification authentication equipment through a bidirectional authentication security channel by means of the mapping relation between the personal account in the bidirectional authentication updating certificate and the biological identification authentication equipment.
Further, the bidirectional authentication security channel can prevent a malicious body from stealing or falsifying data, and periodically update security authentication information of the authentication device and the personal account system, such as certificates, keys and the like, so as to cope with possible security threats and loopholes, and further check scenic spot tickets of the user based on biological characteristics of the user in the biological recognition authentication device, so that the user can pass through scenic spots efficiently.
S3, acquiring real-time video data of the target tourist, determining target authentication equipment in the biological recognition authentication equipment according to a storage path of the real-time video data, and extracting target multidimensional biological characteristics of the target tourist in the real-time video data.
In the embodiment of the invention, the real-time video data is a section of video data randomly shot by the target tourist, wherein the real-time video data of the target tourist can be acquired from a pre-stored storage area through computer sentences (such as Java sentences, python sentences and the like) with a data grabbing function.
Further, to enable multi-device verification of the target guest, it may be determined in which biometric authentication device the target guest wants to authenticate based on the stored path of the real-time video data to ensure efficient authentication of the target guest.
In the embodiment of the invention, when the user uploads the implementation video data to the biological identification authentication device, the back-end interface stores the video data to different devices or stores the video data to different devices according to the device identification, if a target tourist authenticates in the face recognition device of the scenic spot, the authentication device stores the face information of the user; the target tourist authenticates in the fingerprint identification equipment of the scenic spot, and the authentication equipment stores fingerprint information of the user; in addition, the target guest can also be authenticated in the mobile terminal device, and thus, it is necessary to accurately determine the final authentication device of the target guest, i.e., the target authentication device.
In an embodiment of the present invention, referring to fig. 3, the determining, according to a storage path of the real-time video data, a target authentication device in the biometric authentication device includes:
s31, generating an authentication storage matrix by an authentication device identifier of the biological recognition authentication device and a storage path of the biological recognition authentication device;
s32, carrying out path analysis on the storage path of the real-time video data to obtain a path analysis identifier;
s33, matching the path analysis identifier with the identifier storage mapping relation in the authentication storage matrix to obtain a matching logic value;
and S34, when the matching logic value is equal to a preset target matching threshold value, determining target authentication equipment in the biological identification authentication equipment.
In detail, the unique identification (such as the device ID) of each biometric authentication device is associated with the corresponding real-time video data storage path, that is, when the real-time video data is stored, the device identification may be used as a part of the information of the storage path, when the target authentication device needs to be determined, the device identification information contained in the real-time video data may be parsed according to the storage path of the real-time video data, so as to determine the authentication device generating the video data, the parsed device identification is matched with the identification of the biometric authentication device known in the system, so as to determine the target authentication device, that is, the path identification information in the real-time video data is contained in the storage path of the identification storage mapping relationship in the authentication storage matrix, the matching logic value is set to 1, when the path identification information in the implementation video data is not contained, the matching logic value is set to 0, and when only the matching logic value is 1, the device with the matching logic value of 1 in the biometric authentication device is determined as the target authentication device.
Specifically, the storage path of the real-time video data is "/root/devices 123/devices/", where "device123" is a device identifier, the target authentication device can be determined to be a biometric authentication device with a device ID of "device123" by analyzing the storage path, and the authentication device corresponding to the real-time video data can be determined based on the storage path, so that accurate management and operation on an application scenario are realized.
Further, based on the real-time video data of the target tourist, the multidimensional biological characteristics of the target tourist can be extracted, the authenticity of the target tourist is ensured, the biological characteristics of the user are extracted in a dynamic image, and the authenticity of the biological characteristics is ensured.
In the embodiment of the invention, the target multidimensional biological characteristics are the facial characteristics and the fingerprint characteristics of the target tourists, so that the authenticity of the target tourists can be ensured, and the accuracy of checking the scenic spot entrance tickets can be improved.
In the embodiment of the present invention, the extracting the target multidimensional biological feature of the target tourist in the real-time video data includes:
extracting video frame data of the real-time video data;
performing semantic segmentation on the video frame data to obtain pixel semantic categories of the video frame data;
Determining an eye pixel optical flow vector of the video frame data according to the pixel semantic category;
calculating a dynamic value of the real-time video data according to the eye pixel optical flow vector, wherein the dynamic value calculation formula is as follows:
wherein T is the dynamic value, B is the semantic weight of the eye pixel, x is the pixel abscissa, and y is the pixel ordinate，L is the brightness of the eye pixels, V is the eye pixel optical flow vector, t i N is the frame length of the video frame data;
when the dynamic value is equal to a preset target dynamic threshold value, collecting target face information characteristics and target fingerprint information characteristics of the target tourists;
and carrying out feature fusion on the target face information features and the target fingerprint information features to obtain target multidimensional biological features of the target tourists.
In detail, the real-time video data is divided into frames, so that video frame data of the real-time video data are extracted, the video frame data of the real-time video data can be extracted through a computer sentence with a data grabbing function, further, the pixel values of the video frame data are subjected to semantic segmentation to obtain pixel semantic categories of the video frame data, wherein the image is subjected to semantic segmentation, each pixel point in the image is distributed into corresponding semantic categories, a pre-trained semantic segmentation model such as FCN (Fully Convolutional Network, a completely convolved network structure), U-Net (encoder), deep Lab (deep convolved neural network) and the like can be utilized for semantic segmentation, further, optical flow analysis is carried out on the eye features of a target tourist based on the result of the semantic segmentation, the authenticity of biological features can be ensured, the optical flow analysis can be used for calculating the displacement condition of each pixel point in the image by tracking pixel changes among continuous frames, and the displacement vector of each pixel point in the image can be obtained through optical flow analysis, so that the motion track and speed information of an object can be known.
Specifically, calculating the eye dynamic value of the target tourist in the real-time video data according to the eye pixel optical flow vector, wherein B (x, y) represents the semantic weight of the pixel at the (x, y) position, represents the semantic weight of the eye, and L (x, y, t) i ) Representing pixel brightness at the (x, y) position at the ith frame time, V (x, y, t) i ) Pixel optical flow vector representing the ith frame time at the (x, y) positionThe value of the pixel light flow vector value comprises the square sum of the pixel light flow in the horizontal direction and the pixel light flow in the vertical direction, then the eye dynamic value of the real-time video data can be calculated, when the dynamic value is 0, the target tourist is shown to be dynamic, the identity of the target tourist is real, then the target face information characteristic and the target fingerprint information characteristic of the target tourist are collected, further the target face information characteristic and the target fingerprint information characteristic are fused, the target multidimensional biological characteristic of the target tourist is obtained, when the dynamic value is not equal to the preset target dynamic threshold value 0, the real-time video data of the target tourist is obtained again, and then the calculation is carried out again until the dynamic value is equal to the preset target dynamic threshold value.
Further, the movement of objects in the image can be more fully understood by combining the optical flow and the semantic information. The optical flow can provide the motion information of each pixel point in the image, the motion of the object can be semantically interpreted by combining the optical flow and the semantic information, and further the authenticity of the target tourist is ensured according to the comparison between the extracted multidimensional biological characteristics of the target tourist and the multidimensional encrypted biological characteristics pre-stored in the biological authentication and identification equipment.
And S4, calculating an authentication permission value between the target multidimensional biological feature and the multidimensional encrypted biological feature in the target authentication equipment by using a preset bidirectional authentication algorithm, and generating an authentication information matrix of the target tourist according to the authentication permission value.
In the embodiment of the invention, the authentication permission value refers to a comparison value obtained by comparing and matching the target multidimensional biological characteristics with the multidimensional encryption biological characteristics in the target authentication equipment, and is used for evaluating the true identity of the target tourist and judging whether the identity authentication of the target authentication equipment can be passed.
In the embodiment of the present invention, the calculating, by using a preset bidirectional authentication algorithm, an authentication permission value between the target multidimensional biometric and the multidimensional encrypted biometric in the target authentication device includes:
decrypting the multi-dimensional encrypted biometric to obtain a multi-dimensional authenticated biometric;
calculating an authentication grant value between the target multi-dimensional biometric and the multi-dimensional authentication biometric using a two-way authentication algorithm as follows:
wherein Q is the authentication grant value, alpha k For the kth dimension feature value, beta, in the target multidimensional biological feature k And h is a forward feedback factor, g is a reverse feedback factor, and m is a feature dimension for the kth dimension characteristic value in the multidimensional authentication biological characteristic.
In detail, before comparing the target multidimensional biological feature with the multidimensional encrypted biological feature in the target authentication device, the multidimensional encrypted biological feature needs to be decrypted, then the multidimensional encrypted biological feature is decrypted based on the hidden decryption key, and the encryption process is operated in reverse to obtain the multidimensional authentication biological feature, so that an authentication permission value between the target multidimensional biological feature and the multidimensional authentication biological feature is calculated.
Specifically, the target multi-dimensional biological feature is compared with the multi-dimensional authentication biological feature in the two-way authentication algorithm, namely alpha k -β k The multidimensional authentication biological feature is fed back to a forward feedback factor h of the target multidimensional biological feature to indicate whether authentication is successful or not; the multi-dimensional authentication biological feature and the target multi-dimensional biological feature can be reversely authenticated, namely beta k -α k The target multidimensional biological feature is fed back to the multidimensional authentication biological feature by an inverse feedback factor g to indicate whether authentication is successful or not, and when h and g are 1, authentication is successful; when h and g are tree values other than 1, authentication failure is indicated, and the value of the authentication permission value Q is zero, indicating that both sides authentication is successful.
Further, the permission of the target guest's authentication device may be determined according to the authentication permission value, and the target guest may have more than one target authentication, so that it is necessary to construct a mapping relationship between the permission value and the target authentication device, and to timely grasp the authentication dynamics of the target guest.
In the embodiment of the invention, the authentication information matrix refers to a mapping relationship between a permission value and target authentication equipment based on authentication information of target tourists.
In the embodiment of the present invention, the generating the authentication information matrix of the target guest according to the authentication permission value includes:
extracting the authentication information of the target tourist according to the authentication permission value;
determining the authentication authority information of the target tourist according to the authentication information;
and generating an authentication information matrix of the target tourist according to the authentication authority information and the authentication permission value.
In detail, according to the authentication permission value, an authentication information matrix of the target guest can be generated, wherein the authentication information matrix comprises identity information, permission value, authentication equipment and corresponding authority information of the target guest, after the target guest receives the authentication permission value, a public key of a server is used for verifying the validity of the permission value, after the authentication is passed, corresponding authentication information which possibly comprises related information such as a digital signature, a timestamp and the like is extracted from the permission value, according to the extracted authentication information, the identity of the target guest is confirmed, the specific user ID, the user name and the like can be obtained, once the identity of the target guest is confirmed, a corresponding authority matrix comprising access authority, operation authority and the like owned by the user can be generated according to the authority information corresponding to the identity, finally, the authentication information matrix can be generated according to the identity and the authority information of the target guest, the identity information and the authentication equipment are integrated together, and the identity information of the target guest and the authentication equipment are used for subsequent access control and operation authorization.
Further, according to the corresponding relation between the permission value and the authentication equipment in the authentication information matrix, the verification value of the final cross-equipment verification scenic spot ticket of the target tourist can be determined, so that cross-equipment verification is realized.
S5, calculating ticket verification values of the target tourists according to the authentication information matrix through a preset dissimilating algorithm, and updating the authentication information matrix when the ticket verification values are smaller than a preset verification threshold value until the ticket verification values are larger than or equal to the preset verification threshold value.
In the embodiment of the invention, the ticket verification value refers to the final scenic spot ticket verification result of the target tourist based on different authentication devices.
In the embodiment of the present invention, the calculating, by a preset dissimilating algorithm, the ticket verification value of the target tourist according to the authentication information matrix includes:
determining an authentication influence factor of the scenic spot ticket verification according to the authentication information matrix;
determining an authentication permission weight corresponding to the authentication permission value in the authentication information matrix according to the authentication influence factor;
calculating ticket verification values of the target tourists according to the authentication permission weights and the authentication permission values through the following dissimilating algorithm:
Wherein M is the ticket verification value, lambda is the control factor of the external factor, gamma e For verification of extrinsic factors, delta d Authentication permission weight for the d-th authentication device, H d The authentication permission value for the D-th authentication device, E is the number of factors of the extrinsic factors, and D is the number of authentication devices.
In detail, the authentication influencing factors refer to factors influencing authentication permission values, such as user permission levels, the number of user authentication devices and the time of reservation of user tickets, and then the authentication permission weights corresponding to the authentication permission values are determined according to the authentication influencing factors by using a preset analytic hierarchy process, namely, each authentication influencing factor is assigned with a weight to represent the relative importance of each authentication influencing factor, the weight is usually a real number ranging from 0 to 1, and the sum should be equal to 1. The higher weight indicates that the factor is more important, and then the ticket verification value of the target tourist is determined according to the authentication permission weight and the authentication permission value.
Specifically, the extrinsic factor control factor λ in the dissimilating algorithm refers to whether an extrinsic influence factor exists, and if no extrinsic influence factor exists, λ=0; if there are external influencing factors, λ=1, where the external factors include failure rate of the authentication device, network connection problem of the authentication device, data storage problem of the authentication device, power problem of the authentication device, etc., verification values of different external factors are set by user definition based on different external influencing factors, and then ticket verification values of target tourists based on different authentication devices are determined under the condition of considering the external factors, so that scenic spot ticket verification across devices can be implemented.
Further, when the ticket verification value is smaller than a preset verification threshold, returning to the step of calculating the authentication permission value between the target multi-dimensional biological feature and the multi-dimensional encrypted biological feature in the target authentication device by using a preset bidirectional authentication algorithm, updating the authentication information matrix based on the recalculated authentication permission value, and updating the mapping relation between the authentication permission value and the authentication device in the authentication information matrix again until the ticket verification value is larger than or equal to the preset verification threshold.
And S6, when the ticket verification value is greater than or equal to a preset verification threshold value, generating a ticket verification license of the target tourist.
In the embodiment of the invention, when the ticket verification value is greater than or equal to the preset verification threshold value, the target tourist can pass through, the ticket verification license of the target tourist is generated, the ticket verification license of the target tourist is indicated to pass through the ticket verification, related services can be entered or enjoyed, a ticket verification license is generated, the license can be in an electronic form, such as a two-dimensional code displayed on a mobile phone, the license possibly contains information of identity information, verification time, place and the like of the tourist, the system informs the tourist of successful verification, and the license is provided, and the target tourist can be informed through mobile application, short message, electronic mail or other communication modes, so that the scenic spot ticket non-inductive verification of the target tourist is completed.
According to the embodiment of the invention, the multidimensional biological characteristics of the target user are extracted, so that the multidimensional biological characteristics are encrypted, and the safety of multidimensional biological characteristic storage is improved; synchronously storing the multidimensional encrypted biological characteristics into a pre-constructed personal account and synchronously updating and sending the multidimensional encrypted biological characteristics to biological identification authentication equipment, so that possible security threats and possible loopholes can be dealt with; the target authentication equipment is determined based on the real-time video data of the target tourist, and the target multidimensional biological characteristics of the target tourist are extracted, so that the authenticity of the target tourist can be ensured, and the accuracy of checking the scenic spot entrance ticket is improved; calculating an authentication permission value between the target vitamin characteristic and the multidimensional encryption biological characteristic in the target authentication equipment, generating an authentication information matrix of the target tourist according to the authentication permission value, and determining a verification value of a final cross-equipment verification scenic spot ticket of the target tourist so as to realize cross-equipment verification; calculating ticket verification values of the target tourists according to the authentication information matrix, and updating the authentication information matrix when the ticket verification values are smaller than verification threshold values, so that the accuracy of ticket verification of the target tourist attraction is improved; when the ticket verification value is greater than or equal to the verification threshold value, generating ticket verification license of the target tourist, and improving the speed of ticket verification in the scenic spot. Therefore, the scenic spot ticket non-inductive verification method, the scenic spot ticket non-inductive verification system and the scenic spot ticket non-inductive verification medium based on the living organism identification can solve the problem that the efficiency is lower when the scenic spot ticket non-inductive verification is carried out.
Fig. 4 is a functional block diagram of a scenic spot ticket non-inductive verification system based on living organism identification according to an embodiment of the invention.
The scenic spot ticket non-inductive verification system 100 based on the living organism identification can be installed in an electronic device. Depending on the functions implemented, the scenic spot ticket non-inductive verification system 100 based on the living organism identification may include a multidimensional biometric encryption module 101, a multidimensional encrypted biometric transmission module 102, a target multidimensional biometric extraction module 103, an authentication information matrix generation module 104, a ticket verification value calculation module 105, and a ticket verification license generation module 106. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the multi-dimensional biological feature encryption module 101 is configured to obtain a basic attribute of a target user, extract a multi-dimensional biological feature of the target user according to the basic attribute, and encrypt the multi-dimensional biological feature by using a preset double encryption algorithm to obtain a multi-dimensional encrypted biological feature;
The multidimensional encryption biometric transmitting module 102 is configured to synchronously store the multidimensional encryption biometric into a pre-established personal account, and synchronously update the multidimensional encryption biometric in the personal account to a preset biometric authentication device;
the target multidimensional biological feature extraction module 103 is configured to obtain real-time video data of a target tourist, determine a target authentication device in the biological recognition authentication device according to a storage path of the real-time video data, and extract a target multidimensional biological feature of the target tourist in the real-time video data;
the authentication information matrix generation module 104 is configured to calculate an authentication permission value between the target multidimensional biometric and the multidimensional encrypted biometric in the target authentication device by using a preset bidirectional authentication algorithm, and generate an authentication information matrix of the target visitor according to the authentication permission value;
the ticket checking value calculating module 105 is configured to calculate a ticket checking value of the target tourist according to the authentication information matrix through a preset dissimilating algorithm, and update the authentication information matrix when the ticket checking value is smaller than a preset checking threshold value until the ticket checking value is greater than or equal to the preset checking threshold value;
The ticket checking license generating module 106 is configured to generate a ticket checking license of the target tourist when the ticket checking value is greater than or equal to a preset checking threshold value.
In detail, each module in the scenic spot ticket non-inductive verification system 100 based on living organism identification in the embodiment of the present invention adopts the same technical means as the scenic spot ticket non-inductive verification method based on living organism identification described in fig. 1 to 3, and can produce the same technical effects, and will not be repeated here.
The present invention also provides a medium storing a computer program which, when executed by a processor of an electronic device, may implement:
acquiring basic attributes of a target user, extracting multidimensional biological characteristics of the target user according to the basic attributes, and encrypting the multidimensional biological characteristics by using a preset double encryption algorithm to obtain multidimensional encrypted biological characteristics;
synchronously storing the multidimensional encryption biological characteristics into a pre-built personal account, and synchronously updating the multidimensional encryption biological characteristics in the personal account and transmitting the multidimensional encryption biological characteristics to preset biological identification authentication equipment;
Acquiring real-time video data of a target tourist, determining target authentication equipment in the biological recognition authentication equipment according to a storage path of the real-time video data, and extracting target multidimensional biological characteristics of the target tourist in the real-time video data;
calculating an authentication permission value between the target multi-dimensional biological feature and the multi-dimensional encrypted biological feature in the target authentication equipment by using a preset bidirectional authentication algorithm, and generating an authentication information matrix of the target tourist according to the authentication permission value;
calculating ticket verification values of the target tourists according to the authentication information matrix through a preset dissimilating algorithm, and updating the authentication information matrix when the ticket verification values are smaller than a preset verification threshold value until the ticket verification values are larger than or equal to the preset verification threshold value;
and when the ticket verification value is greater than or equal to a preset verification threshold value, generating a ticket verification license of the target tourist.
In the several embodiments provided by the present invention, it should be understood that the disclosed methods, systems, and media may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and other manners of division may be implemented in practice.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the foregoing description, and all changes which come within the meaning and range of equivalency of the scope of the invention are therefore intended to be embraced therein.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. Multiple units or systems as set forth in the system claims may also be implemented by means of one unit or system in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims (10)

1. A scenic spot ticket non-inductive verification method based on living organism identification, characterized in that the method comprises the following steps:
S1, acquiring basic attributes of a target user, extracting multidimensional biological characteristics of the target user according to the basic attributes, and encrypting the multidimensional biological characteristics by using a preset double encryption algorithm to obtain multidimensional encrypted biological characteristics;
s2, synchronously storing the multidimensional encryption biological characteristics into a pre-built personal account, and synchronously updating the multidimensional encryption biological characteristics in the personal account and sending the multidimensional encryption biological characteristics to preset biological identification authentication equipment;
s3, acquiring real-time video data of a target tourist, determining target authentication equipment in the biological recognition authentication equipment according to a storage path of the real-time video data, and extracting target multidimensional biological characteristics of the target tourist in the real-time video data;
s4, calculating an authentication permission value between the target multi-dimensional biological feature and the multi-dimensional encrypted biological feature in the target authentication equipment by using a preset two-way authentication algorithm, and generating an authentication information matrix of the target tourist according to the authentication permission value, wherein the calculating of the authentication permission value between the target multi-dimensional biological feature and the multi-dimensional encrypted biological feature in the target authentication equipment by using the preset two-way authentication algorithm comprises the following steps:
Decrypting the multi-dimensional encrypted biometric to obtain a multi-dimensional authenticated biometric;
calculating an authentication grant value between the target multi-dimensional biometric and the multi-dimensional authentication biometric using a two-way authentication algorithm as follows:
wherein Q is the authentication grant value, alpha k For the kth dimension feature value, beta, in the target multidimensional biological feature k For the k-th dimension characteristic value in the multidimensional authentication biological characteristic, h is a forward feedback factor, g is a reverse feedback factor, and m is a characteristic dimension;
s5, calculating ticket verification values of the target tourists according to the authentication information matrix through a preset dissimilating algorithm, and updating the authentication information matrix when the ticket verification values are smaller than a preset verification threshold value until the ticket verification values are larger than or equal to the preset verification threshold value;
and S6, when the ticket verification value is greater than or equal to a preset verification threshold value, generating a ticket verification license of the target tourist.
2. The method of non-inductive verification of scenic spots tickets based on living organism identification according to claim 1, wherein said extracting the multi-dimensional biometric features of the target user based on the basic attributes comprises:
Extracting the unique identity of the target user from the basic attribute;
collecting the face information characteristics and fingerprint information characteristics of the target user according to the unique identity;
and carrying out feature fusion on the face information features and the fingerprint information features to obtain the multidimensional biological features of the target user.
3. The method for non-inductive verification of scenic spot tickets based on living organism identification according to claim 1, wherein encrypting the multi-dimensional biological feature by using a preset double encryption algorithm to obtain a multi-dimensional encrypted biological feature comprises:
performing feature coding on the multidimensional biological feature to obtain a multidimensional biological coding feature;
generating a hidden encryption key according to the multidimensional biological coding characteristics and a preset target sequence;
generating a ciphertext encryption information factor according to the hidden encryption key and the target sequence;
encrypting the multidimensional biological feature according to the hidden encryption key and the ciphertext encryption information factor by using a double encryption algorithm as follows to obtain the multidimensional encrypted biological feature:
wherein P is the multi-dimensional encrypted biometric, A is the multi-dimensional biometric, delta is the hidden encryption key, Is the exclusive or operation sign, q is the sign factor, r 2 And encrypting a second target sequence in the information factor for the ciphertext, wherein omega is an information encryption embedded vector.
4. The method for non-inductive verification of scenic spot tickets based on living organism identification according to claim 1, wherein said transmitting the multi-dimensional encrypted biometric update in the personal account to a preset biometric authentication device comprises:
generating a bidirectional authentication contract between the biometric authentication device and the personal account according to the authentication device identifier of the biometric authentication device;
constructing a bidirectional authentication security channel between the biometric authentication device and the personal account according to the bidirectional authentication contract;
extracting a bidirectional authentication update certificate of the bidirectional authentication contract according to a preset timestamp;
and synchronously updating the multidimensional encrypted biological characteristics through the bidirectional authentication security channel and the bidirectional authentication updating certificate and sending the multidimensional encrypted biological characteristics to the biological identification authentication equipment.
5. The method of non-inductive verification of scenic spot tickets based on biometric identification as in claim 1, wherein said determining a target authentication device of said biometric authentication devices from a stored path of said real-time video data comprises:
Generating an authentication storage matrix by an authentication device identifier of the biometric authentication device and a storage path of the biometric authentication device;
carrying out path analysis on the storage path of the real-time video data to obtain a path analysis identifier;
matching the path analysis identifier with the identifier storage mapping relation in the authentication storage matrix to obtain a matching logic value;
and when the matching logic value is equal to a preset target matching threshold value, determining target authentication equipment in the biological identification authentication equipment.
6. The method of non-inductive verification of scenic spot tickets based on living organism identification as set forth in claim 1, wherein said extracting the target multidimensional biometric of the target guest in the real-time video data comprises:
extracting video frame data of the real-time video data;
performing semantic segmentation on the video frame data to obtain pixel semantic categories of the video frame data;
determining an eye pixel optical flow vector of the video frame data according to the pixel semantic category;
calculating a dynamic value of the real-time video data according to the eye pixel optical flow vector, wherein the dynamic value calculation formula is as follows:
Wherein T is the dynamic value, and B is the semantic weight of the eye pixelX is the pixel abscissa, y is the pixel ordinate,l is the brightness of the eye pixels, V is the eye pixel optical flow vector, t i N is the frame length of the video frame data;
when the dynamic value is equal to a preset target dynamic threshold value, collecting target face information characteristics and target fingerprint information characteristics of the target tourists;
and carrying out feature fusion on the target face information features and the target fingerprint information features to obtain target multidimensional biological features of the target tourists.
7. The method of non-inductive verification of scenic spot tickets based on living organism identification as set forth in claim 1, wherein the generating the authentication information matrix of the target tourist from the authentication permission values includes:
extracting the authentication information of the target tourist according to the authentication permission value;
determining the authentication authority information of the target tourist according to the authentication information;
and generating an authentication information matrix of the target tourist according to the authentication authority information and the authentication permission value.
8. The method for non-inductive verification of scenic spot tickets based on living organism identification according to claim 1, wherein said calculating ticket verification values of the target tourists according to the authentication information matrix by a preset dissimilating algorithm comprises:
Determining an authentication influence factor of the scenic spot ticket verification according to the authentication information matrix;
determining an authentication permission weight corresponding to the authentication permission value in the authentication information matrix according to the authentication influence factor;
calculating ticket verification values of the target tourists according to the authentication permission weights and the authentication permission values through the following dissimilating algorithm:
wherein M is the ticket verification value, lambda is the control factor of the external factor, gamma e For verification of extrinsic factors, delta d Authentication permission weight for the d-th authentication device, H d The authentication permission value for the D-th authentication device, E is the number of factors of the extrinsic factors, and D is the number of authentication devices.
9. A scenic spot ticket non-inductive verification system based on living organism identification for performing the scenic spot ticket non-inductive verification method based on living organism identification as claimed in any one of claims 1-8, the system comprising:
the multi-dimensional biological feature encryption module is used for acquiring basic attributes of a target user, extracting multi-dimensional biological features of the target user according to the basic attributes, and encrypting the multi-dimensional biological features by using a preset double encryption algorithm to obtain multi-dimensional encrypted biological features;
The multi-dimensional encryption biological feature transmitting module is used for synchronously storing the multi-dimensional encryption biological features into a pre-built personal account and synchronously updating the multi-dimensional encryption biological features in the personal account and transmitting the multi-dimensional encryption biological features into a pre-set biological identification authentication device;
the target multidimensional biological feature extraction module is used for acquiring real-time video data of a target tourist, determining target authentication equipment in the biological recognition authentication equipment according to a storage path of the real-time video data, and extracting target multidimensional biological features of the target tourist in the real-time video data;
an authentication information matrix generation module, configured to calculate an authentication permission value between the target multi-dimensional biometric feature and the multi-dimensional encrypted biometric feature in the target authentication device using a preset mutual authentication algorithm, and generate an authentication information matrix of the target guest according to the authentication permission value, where the calculating, using the preset mutual authentication algorithm, the authentication permission value between the target multi-dimensional biometric feature and the multi-dimensional encrypted biometric feature in the target authentication device includes:
decrypting the multi-dimensional encrypted biometric to obtain a multi-dimensional authenticated biometric;
Calculating an authentication grant value between the target multi-dimensional biometric and the multi-dimensional authentication biometric using a two-way authentication algorithm as follows:
wherein Q is the authentication grant value, alpha k For the kth dimension feature value, beta, in the target multidimensional biological feature k For the k-th dimension characteristic value in the multidimensional authentication biological characteristic, h is a forward feedback factor, g is a reverse feedback factor, and m is a characteristic dimension;
the ticket checking value calculating module is used for calculating ticket checking values of the target tourists according to the authentication information matrix through a preset dissimilating algorithm, and updating the authentication information matrix until the ticket checking values are larger than or equal to a preset checking threshold when the ticket checking values are smaller than the preset checking threshold;
and the ticket checking license generation module is used for generating the ticket checking license of the target tourist when the ticket checking value is greater than or equal to a preset checking threshold value.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the scenic spot ticket non-inductive verification method based on living organism identification as claimed in any one of claims 1 to 8.
CN202311516872.9A 2023-11-14 2023-11-14 Scenic spot ticket non-inductive verification method, system and medium based on living organism identification Pending CN117494092A (en)

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