CN112561525A - Block chain biological face recognition method and system - Google Patents

Block chain biological face recognition method and system Download PDF

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CN112561525A
CN112561525A CN202011488855.5A CN202011488855A CN112561525A CN 112561525 A CN112561525 A CN 112561525A CN 202011488855 A CN202011488855 A CN 202011488855A CN 112561525 A CN112561525 A CN 112561525A
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data
facial recognition
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characteristic data
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赖健行
刘炜
黄国良
张翼
黄盛威
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Shenzhen Great China Blockchain Technology Co ltd
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Shenzhen Great China Blockchain Technology Co ltd
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Abstract

The invention provides a block chain biological face recognition method and system, and relates to the field of block chains. A block chain biological face recognition method comprises the following steps: acquiring mnemonic words according to a one-time random algorithm; verifying the mnemonic words and judging whether recording is carried out or not; collecting biological face identification characteristic data, and encrypting the biological face identification characteristic data and the verified mnemonic words through hash calculation to obtain a key pair; data of the key pair is uploaded to distributed blocks, and the nearest node is automatically selected according to the P2P network protocol. The biological face recognition data can be encrypted to the block chain, the data cannot be tampered, and the face recognition identity is asymmetrically encrypted based on public and private keys. In addition, the invention also provides a block chain biological face recognition system, which comprises: the device comprises a first acquisition module, a verification module, a second acquisition module, an uploading module, a query module, a comparison module and a verification password pair module.

Description

Block chain biological face recognition method and system
Technical Field
The invention relates to the field of block chains, in particular to a block chain biological face recognition method and a block chain biological face recognition system.
Background
The existing biological face recognition data storage belongs to the traditional internet storage. One is stored locally at the client and the other is the presence server. Both of them have a common defect whether existing locally or in the server, and are easy to be tampered, once other people take the biological identification data and make changes, the assets of the user can be stolen, and the loss of the user cannot be measured.
Blockchains can be used for automation tasks and processes not limited to the field of cryptocurrency, and such a solution would enable better cryptographic processing of transactions using the properties of blockchains. The current distribution and transaction in the market are not transparent, and the public credibility in the consumer market is not enough. All publications in the market have a serious centralization phenomenon, and the publications are popularized by respective enterprises or platforms no matter whether credit cards, aviation flights, shopping in shopping malls or online shopping malls in the telecommunication industry. For the consumer, the reliability of the transaction is pending.
Disclosure of Invention
The invention aims to provide a block chain biological face recognition method, which can encrypt biological face recognition data to a block chain, the data cannot be falsified, and the face recognition identity adopts asymmetric encryption based on public and private keys and digital signature to ensure the authenticity of a recognition information source.
Another objective of the present invention is to provide a blockchain biometric facial recognition system, which is capable of operating a blockchain biometric facial recognition method.
The embodiment of the invention is realized by the following steps:
in a first aspect, an embodiment of the present application provides a block chain biological face recognition method, which includes obtaining mnemonics according to a one-time stochastic algorithm; verifying the mnemonic words and judging whether recording is carried out or not; collecting biological face identification characteristic data, and encrypting the biological face identification characteristic data and the verified mnemonic words through hash calculation to obtain a key pair; uploading the data of the key pair to a distributed block, automatically selecting the nearest node according to a P2P network protocol, and synchronizing the data by the node according to the distributed protocol; inquiring identical or similar biological facial recognition characteristic data in a database according to the acquired biological facial recognition characteristic data, decrypting a digital certificate attached to the inquired biological facial recognition characteristic data to obtain a corresponding public key, and decrypting a digital signature attached to the inquired biological facial recognition characteristic data into a first abstract by using the public key; performing hash operation on the biological face recognition feature data of the current visitor to obtain a second abstract, comparing whether the first abstract and the second abstract are equal, and if so, allowing the visitor to access the transaction node; and the obtained key pair corresponds to the protection password set by the user, so that the correspondence between the biological information of the user, the key pair and the protection password is completed.
In some embodiments of the present invention, in the above uploading data of the key pair to the distributed blocks, the closest node is automatically selected according to the P2P network protocol, and after the synchronization of the data by the nodes according to the distributed protocol, the method further includes: verifying the authenticity of the secret key and storing the public key for the user with the history record, and acquiring the biological face identification data when the user logs in again, namely executing a decryption login program.
In some embodiments of the present invention, in the above uploading data of the key pair to the distributed blocks, the closest node is automatically selected according to the P2P network protocol, and after the synchronization of the data by the nodes according to the distributed protocol, the method further includes: and performing Hash operation on the biological face identification characteristic data to obtain a first abstract, and pre-storing a digital signature and a digital certificate corresponding to the first abstract.
In some embodiments of the present invention, the above further includes that the first digest, the digital signature and the digital certificate are recorded in each transaction node by block chain distributed packaging.
In some embodiments of the present invention, the foregoing further includes setting an access control module on each transaction node, where the access control module performs authority management on an accessor accessing the transaction node.
In some embodiments of the invention, the foregoing further comprises opening different levels of permission for different levels of users when the visitor accesses the transaction node, the levels of permission being associated with the biometric facial recognition feature data.
In some embodiments of the present invention, the transaction node is interfaced with a third party monitoring system, and the third party monitoring system is used to encrypt a public key corresponding to the private key to obtain the digital certificate.
In some embodiments of the present invention, the acquiring the biometric facial recognition feature data includes: and collecting biological facial recognition features by adopting a MongoDB database.
In a second aspect, an embodiment of the present application provides a block chain biometric facial recognition system, which includes a first obtaining module, configured to obtain a mnemonic word according to a one-time random algorithm; the verification module is used for verifying the mnemonics and judging whether to record or not; the second acquisition module is used for acquiring biological face identification characteristic data, and encrypting the biological face identification characteristic data and the verified mnemonic words through hash calculation to obtain a key pair; the uploading module is used for uploading the data of the key pair to the distributed blocks, automatically selecting the nearest node according to a P2P network protocol, and synchronizing the data by the node according to the distributed protocol; the inquiry module is used for inquiring the same or similar biological facial recognition characteristic data in the database according to the collected biological facial recognition characteristic data, decrypting a digital certificate attached to the inquired biological facial recognition characteristic data to obtain a corresponding public key thereof, and decrypting a digital signature attached to the inquired biological facial recognition characteristic data into a first abstract by using the public key; the comparison module is used for carrying out hash operation on the biological face recognition feature data of the current visitor to obtain a second abstract, comparing whether the first abstract and the second abstract are equal or not, and if so, granting the visitor access to the transaction node; and the password pair verifying module is used for corresponding the obtained key pair with the protection password set by the user to complete the correspondence between the biological information of the user, the key pair and the protection password.
In some embodiments of the invention, the above includes at least one memory for storing computer instructions; at least one processor in communication with the memory, wherein the at least one processor, when executing the computer instructions, causes the system to: the device comprises a first acquisition module, a verification module, a second acquisition module, an uploading module, a query module, a comparison module and a verification password pair module.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
the biological face recognition data can be encrypted into a block chain, the data cannot be tampered, the face recognition identity is asymmetrically encrypted based on public and private keys, and authenticity of a recognition information source is guaranteed through digital signatures. Whether the biological facial recognition feature data of the current visitor are consistent with the biological facial recognition feature data inquired from the database or not can be known by comparing the first abstract with the second abstract, and the matching accuracy of the biological facial recognition feature data is ensured by triple encryption of Hash operation, digital signature and digital certificate; and because the hash operation obtains the irreversible characteristic of the abstract, the biological face identification characteristic data corresponding to the first abstract is prevented from being tampered, and as long as the first abstract is the same as the second abstract, the inquired biological face identification characteristic data can be judged not to be tampered and is matched with the biological face identification characteristic data of the visitor to be visited at present, the transaction security of the visitor is guaranteed, and the security of the biological face identification characteristic data in the database is guaranteed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a block-chain biometric facial recognition method according to an embodiment of the present invention;
FIG. 2 is a block chain biological face recognition method according to an embodiment of the present invention;
fig. 3 is a block chain biometric facial recognition system module according to an embodiment of the present invention.
Icon: 10-a first acquisition module; 20-a verification module; 30-a second acquisition module; 40-an upload module; 50-a query module; 60-an alignment module; 70-authentication password pair module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the individual features of the embodiments can be combined with one another without conflict.
Example 1
Referring to fig. 1, fig. 1 is a schematic diagram of a block chain biological face recognition method according to an embodiment of the present invention, which includes the following steps:
s100, acquiring mnemonics according to a one-time random algorithm;
specifically, the mnemonic is another expression of the plaintext private key, which was originally proposed by the specification of BIP39, and the purpose of the mnemonic is to help the user memorize the complex private key (64-bit hash value). The mnemonic words are generally composed of 12, 15, 18 and 21 words, the words are taken from a fixed word stock, the generation sequence of the words is also according to a certain algorithm, so that a user does not need to worry about randomly inputting 12 words to generate an address.
In some embodiments, the user enters the system, which generates 12 mnemonics using the BIP39 specification, called entropy. The mnemonic must entropy encode the words as a multiple of 32 bits. As entropy increases, security improves, but the sentence length of the mnemonics increases. We refer to the initial entropy length as ENT. The allowed ENT size is 128-256 bits. This will effectively prevent brute force cracking.
Step S110, verifying the mnemonic words and judging whether recording is carried out or not;
in some embodiments, before verification, the user stores the mnemonics by himself, the system program identifies that the user operates the mnemonics which are recorded, and the mnemonics are cached according to the original arrangement by utilizing the self-contained cache function of the mobile terminal; the system program randomly positions four sequence bits of the mnemonic words according to a common random algorithm; and the user inputs the words corresponding to the randomly appeared sequence positions in a one-to-one correspondence mode according to the arrangement sequence of the mnemonic words.
Step S120, collecting biological face identification characteristic data, encrypting the biological face identification characteristic data and the verified mnemonic words through hash calculation to obtain a key pair;
in some embodiments, the client camera is used for collecting facial feature data of a user, the encryption algorithm is used for encrypting the biological facial feature data, the obtained ciphertext and the mnemonic words are encrypted by the elliptic curve encryption algorithm, and the elliptic curve signature algorithm, the public key and private key generation algorithm and the elliptic curve key exchange can be automatically executed by the encryption algorithm.
Step S130, uploading the data of the key pair to a distributed block, automatically selecting the nearest node according to a P2P network protocol, and synchronizing the data by the node according to the distributed protocol;
specifically, the PSP is a communication mechanism in the blockchain system, and includes a networking mechanism, a data propagation mechanism, and a data verification mechanism.
In some embodiments, the system uploads the corresponding data to the distributed blocks, the system automatically selects the nearest node according to the P2P network protocol, and the node synchronizes the data according to the distributed protocol.
Step S140, inquiring identical or similar biological facial recognition characteristic data in a database according to the collected biological facial recognition characteristic data, decrypting a digital certificate attached to the inquired biological facial recognition characteristic data to obtain a corresponding public key, and decrypting a digital signature attached to the inquired biological facial recognition characteristic data into a first abstract by using the public key;
step S150, carrying out Hash operation on the biological face recognition characteristic data of the current visitor to obtain a second abstract, comparing whether the first abstract and the second abstract are equal, and if so, granting the visitor access to the transaction node;
in some embodiments, the method comprises the steps of collecting biological facial recognition characteristic data of a visitor, inquiring the same or similar biological facial recognition characteristic data in a database, decrypting a digital certificate attached to the inquired biological facial recognition characteristic data to obtain a corresponding public key, and decrypting a digital signature attached to the inquired biological facial recognition characteristic data into a first abstract by using the public key;
and performing hash operation on the biological face recognition feature data of the current visitor to obtain a second abstract, comparing whether the first abstract and the second abstract are equal, and if so, allowing the visitor to access the transaction node. Uploading the abstract, the digital signature and the digital certificate of the biological facial recognition characteristic data to a network;
the visitor can operate his own account at any transaction node to carry out transaction, the transaction node can be, for example, an intelligent terminal and other devices capable of carrying out transaction operation, the transaction nodes can be intelligent terminals arranged at different transaction points, the visitor operates the intelligent terminal to carry out transaction, and the transaction nodes count transaction data.
And step S160, the obtained key pair corresponds to the protection password set by the user, and the correspondence between the biological information of the user, the key pair and the protection password is completed.
Specifically, the protection password set by the user is specifically the protection password set by the user according to the self condition, the protection password corresponds to the generated block chain private key after the protection password is set, the protection password is used for protecting the biological information of the user after the protection password is correspondingly set, the biological information is prevented from being leaked, meanwhile, secondary password protection can be carried out on the produced block chain private key, and the user can use the protection password conveniently during transaction.
In some embodiments, the validity of the registration is verified, also called verifying the authenticity of the key. The user needs to input the stored mnemonic words firstly when using the mobile terminal for the first time, then the collection of the biological face recognition characteristics is executed, the system carries out matching decryption according to the private key, the public key and the digital signature generated by the data, and the registration login is completed after the verification and the matching are successful.
Example 2
Referring to fig. 2, fig. 2 is a detailed step diagram of a block chain biometric face recognition method according to an embodiment of the present invention, which is shown as follows:
step S200, collecting biological facial recognition characteristics by adopting a MongoDB database;
step S210, verifying the authenticity of the secret key and storing the public key for the user with the history record, and acquiring the biological face identification data when the user logs in again, namely executing a decryption login program;
step S220, performing Hash operation on the biological face identification characteristic data to obtain a first abstract, and pre-storing a digital signature and a digital certificate corresponding to the first abstract;
step S230, the first abstract, the digital signature and the digital certificate are packaged and recorded in each transaction node in a distributed mode through a block chain;
step S240, an access control module is arranged on each transaction node, and the access control module carries out authority management on an accessor accessing the transaction node;
step S250, when the visitor accesses the transaction node, opening access with different authority levels for users with different levels, wherein the authority levels are associated with the biological facial recognition feature data;
step S260, the transaction node is in butt joint with a third party monitoring system, and a public key corresponding to the private key is encrypted by the third party monitoring system to obtain a digital certificate;
step S270, inquiring identical or similar biological facial recognition characteristic data in a database according to the collected biological facial recognition characteristic data, decrypting a digital certificate attached to the inquired biological facial recognition characteristic data to obtain a corresponding public key, and decrypting a digital signature attached to the inquired biological facial recognition characteristic data into a first abstract by using the public key;
step S280, performing hash operation on the biometric facial recognition feature data of the current visitor to obtain a second abstract, comparing whether the first abstract and the second abstract are equal, and if so, granting the visitor access to the transaction node.
In some embodiments, the extracting and storing of the biometric facial recognition feature data may be as follows: transaction data is counted on a plurality of transaction nodes, biological facial recognition characteristics of visitors are collected during transaction, and specifically, facial structured light can be collected in a plurality of ways, for example, by using a structured light camera.
Then constructing a block chain system, packaging the transaction data and the biological face recognition feature data of all transaction nodes into a block within a preset time period, recording the transaction time, the time for acquiring the biological face recognition feature data, the hash of the transaction data and the hash of the biological face recognition feature data into a block head of the current block as a feature value, and calculating the hash of the current block according to the feature value; constructing blocks generated successively into a block chain; the transaction data and the biological face recognition feature data in the block are downloaded to each transaction node for pure decentralization; therefore, pure decentralization of transaction data and biological facial recognition feature data is realized, and the transaction data and the biological facial recognition feature data are prevented from being tampered;
carrying out Hash operation on the biological facial recognition characteristic data to obtain a first abstract, carrying out private key encryption on the first abstract obtained by calculation to obtain a digital signature, carrying out public key encryption corresponding to the private key to obtain a digital certificate, and attaching the digital signature and the digital certificate to the biological facial recognition characteristic data and uploading the digital signature and the digital certificate to a network;
when a certain transaction node is visited, identity authentication of a visitor is carried out in an AR identification mode, the transaction node can be an intelligent terminal with a display, a face identification interface can be displayed on a display interface of the transaction node, and for example, a face outline is displayed on the display interface to serve as an AR frame for face identification; then, a module for collecting images in the mobile transaction node terminal, for example, a camera (the camera may correspond to the face recognition module) of the mobile transaction node terminal, so that the face image of the visitor to be accessed is moved into the face contour in the display interface, and then face recognition is performed, and after the face image enters the face contour in the display interface, the face can be ensured to be within the recognition range of the face recognition module, thereby preventing the face from not completely entering the recognition range of the transaction node in the recognition process to cause unsuccessful recognition. Wherein the facial image of the mobile visitor may be a human mobile camera or a camera moved by an algorithm, such as automatic rotation of a mechanical algorithm, to look for the visitor's face.
The distributed storage based on the block chain has non-tamper property, transaction time, time for acquiring biological facial recognition characteristic data, hash of the transaction data, and hash of the biological facial recognition characteristic data are added into the block head, and the transaction data and the biological facial recognition characteristic data are added into the block body, so that all related data of the transaction data and the biological facial recognition characteristic data can not be tampered.
The method comprises the steps of taking collected biological facial recognition characteristic data as a reference, inquiring the same or similar biological facial recognition characteristic data in a database, wherein the specific inquiry method can be a comparison algorithm based on data similarity, decrypting through a digital certificate to obtain a public key of the inquired biological facial recognition characteristic data, and decrypting through the public key to obtain a first abstract;
the second abstract is a Hash operation result of biological facial recognition characteristic data of an accessor to be accessed, the first abstract and the second abstract are compared to know whether the biological facial recognition characteristic data of the accessor at present is consistent with the biological facial recognition characteristic data inquired from the database or not, and the matching accuracy of the biological facial recognition characteristic data is ensured through the Hash operation, digital signature and digital certificate triple encryption; and because the hash operation obtains the irreversible characteristic of the abstract, the biological face identification characteristic data corresponding to the first abstract is prevented from being tampered, and as long as the first abstract is the same as the second abstract, the inquired biological face identification characteristic data can be judged not to be tampered and is matched with the biological face identification characteristic data of the visitor to be visited at present, the transaction security of the visitor is guaranteed, and the security of the biological face identification characteristic data in the database is guaranteed.
Biometric facial recognition features of the visitor can be collected in a variety of ways, such as by a facial recognition module.
In some embodiments, further comprising the step of: when the visitor accesses the transaction node, the access control module opens access with different permission levels for users with different levels, and the permission levels are associated with the biological facial recognition feature data; the permission levels include normal users, VIP users, and blacklist users.
The biological face recognition feature data correspond to the authority level of the visitor, and when the visitor accesses a certain transaction node, the access control module can distinguish the authority level of the visitor after recognizing the visitor; after the biological facial recognition features of the visitor are collected, the staff can mark the corresponding authority level on the biological facial recognition feature data, and the authority level and the biological facial recognition feature data are associated by adopting a marking method, wherein the marking method can be a digital signature method for example; uploading the marked biological face recognition feature data to an intelligent contract and packaging the intelligent contract into a block; for example, the authority levels can be divided into common users, VIP users and blacklist users, and different access authorities can be set for users with different authority levels. For example: the common user can inquire the self and can carry out transaction; the VIP user can inquire about all persons, but only can carry out own transaction; the blacklisted user cannot access the transaction node.
Specifically, the transaction node is in butt joint with a third party monitoring system, and a public key corresponding to the private key is encrypted by the third party monitoring system to obtain a digital certificate.
Collecting biological facial recognition characteristics by adopting a MongoDB database; compared with other distributed databases, the MongoDB has more storage advantages, and data can be stored in a binary Json format Bson, so that the data storage format is uniform, and the occupied size of the data is reduced.
Example 3
Referring to fig. 3, fig. 3 is a block chain biological face recognition system module schematic diagram according to an embodiment of the present invention, which is shown as follows:
the first acquisition module 10 is used for acquiring mnemonics according to a one-time random algorithm;
the verification module 20 is configured to verify the mnemonic words and determine whether to record the mnemonic words;
the second obtaining module 30 is configured to collect biometric facial recognition feature data, encrypt the biometric facial recognition feature data and the verified mnemonic word through hash calculation, and obtain a key pair;
the uploading module 40 is used for uploading the data of the key pair to the distributed blocks, automatically selecting the nearest node according to the P2P network protocol, and synchronizing the data by the node according to the distributed protocol;
the inquiry module 50 is used for inquiring the same or similar biological facial recognition characteristic data in a database according to the collected biological facial recognition characteristic data, decrypting a digital certificate attached to the inquired biological facial recognition characteristic data to obtain a corresponding public key thereof, and decrypting a digital signature attached to the inquired biological facial recognition characteristic data into a first abstract by using the public key;
the comparison module 60 is configured to perform hash operation on the biometric facial recognition feature data of the current visitor to obtain a second abstract, compare whether the first abstract and the second abstract are equal, and if so, grant the visitor access to the transaction node;
and the password pair verifying module 70 corresponds the obtained key pair with the protection password set by the user to complete the correspondence between the user biological information, the key pair and the protection password.
Also included are a memory, a processor, and a communication interface, which are electrically connected, directly or indirectly, to each other to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory may be used to store software programs and modules, and the processor may execute various functional applications and data processing by executing the software programs and modules stored in the memory. The communication interface may be used for communicating signaling or data with other node devices.
The Memory may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The processor may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), etc.; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
It will be appreciated that the configuration shown in fig. 3 is merely illustrative and may include more or fewer components than shown in fig. 3, or have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In summary, the block chain biological face recognition method and system provided by the embodiment of the present application can encrypt biological face recognition data to a block chain, the data cannot be tampered, the face recognition identity adopts asymmetric encryption based on public and private keys, and the authenticity of the recognition information source is ensured by a digital signature. Whether the biological facial recognition feature data of the current visitor are consistent with the biological facial recognition feature data inquired from the database or not can be known by comparing the first abstract with the second abstract, and the matching accuracy of the biological facial recognition feature data is ensured by triple encryption of Hash operation, digital signature and digital certificate; and because the hash operation obtains the irreversible characteristic of the abstract, the biological face identification characteristic data corresponding to the first abstract is prevented from being tampered, and as long as the first abstract is the same as the second abstract, the inquired biological face identification characteristic data can be judged not to be tampered and is matched with the biological face identification characteristic data of the visitor to be visited at present, the transaction security of the visitor is guaranteed, and the security of the biological face identification characteristic data in the database is guaranteed.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.

Claims (10)

1. A block chain biological face recognition method is characterized by comprising the following steps:
acquiring mnemonic words according to a one-time random algorithm;
verifying the mnemonic words and judging whether recording is carried out or not;
collecting biological face identification characteristic data, and encrypting the biological face identification characteristic data and the verified mnemonic words through hash calculation to obtain a key pair;
uploading the data of the key pair to a distributed block, automatically selecting the nearest node according to a P2P network protocol, and synchronizing the data by the node according to the distributed protocol;
inquiring identical or similar biological facial recognition characteristic data in a database according to the acquired biological facial recognition characteristic data, decrypting a digital certificate attached to the inquired biological facial recognition characteristic data to obtain a corresponding public key, and decrypting a digital signature attached to the inquired biological facial recognition characteristic data into a first abstract by using the public key;
performing hash operation on the biological face recognition feature data of the current visitor to obtain a second abstract, comparing whether the first abstract and the second abstract are equal, and if so, allowing the visitor to access the transaction node;
and the obtained key pair corresponds to the protection password set by the user, so that the correspondence between the biological information of the user, the key pair and the protection password is completed.
2. The blockchain biometric facial recognition method of claim 1, wherein the uploading of the data of the key pair to the distributed blocks is performed, and the nearest node is automatically selected according to the P2P network protocol, and the synchronization of the data by the nodes according to the distributed protocol further comprises:
verifying the authenticity of the secret key and storing the public key for the user with the history record, and acquiring the biological face identification data when the user logs in again, namely executing a decryption login program.
3. The blockchain biometric facial recognition method of claim 1, wherein the uploading of the data of the key pair to the distributed blocks is performed, and a nearest node is automatically selected according to a P2P network protocol, and the synchronization of the data by the nodes according to the distributed protocol further comprises:
and performing Hash operation on the biological face identification characteristic data to obtain a first abstract, and pre-storing a digital signature and a digital certificate corresponding to the first abstract.
4. The block chain biometric facial recognition method as claimed in claim 3, further comprising:
the first abstract, the digital signature and the digital certificate are recorded in each transaction node through block chain distributed packaging.
5. The block chain biometric facial recognition method as claimed in claim 4, further comprising:
and arranging an access control module on each transaction node, wherein the access control module is used for carrying out authority management on an accessor accessing the transaction node.
6. The block-chain biometric facial recognition method as claimed in claim 5, further comprising:
when the visitor accesses the transaction node, the visitor opens access with different authority levels for users with different levels, and the authority levels are associated with the biological facial recognition characteristic data.
7. The method of claim 6, further comprising:
the transaction node is in butt joint with a third party monitoring system, and the third party monitoring system is utilized to encrypt a public key corresponding to the private key to obtain a digital certificate.
8. The blockchain biometric facial recognition method according to claim 1, wherein the acquiring biometric facial recognition feature data comprises:
and collecting biological facial recognition features by adopting a MongoDB database.
9. A blockchain biometric facial recognition system, comprising:
the first acquisition module is used for acquiring mnemonics according to a one-time random algorithm;
the verification module is used for verifying the mnemonics and judging whether to record or not;
the second acquisition module is used for acquiring biological face identification characteristic data, and encrypting the biological face identification characteristic data and the verified mnemonic words through hash calculation to obtain a key pair;
the uploading module is used for uploading the data of the key pair to the distributed blocks, automatically selecting the nearest node according to a P2P network protocol, and synchronizing the data by the node according to the distributed protocol;
the inquiry module is used for inquiring the same or similar biological facial recognition characteristic data in the database according to the collected biological facial recognition characteristic data, decrypting a digital certificate attached to the inquired biological facial recognition characteristic data to obtain a corresponding public key thereof, and decrypting a digital signature attached to the inquired biological facial recognition characteristic data into a first abstract by using the public key;
the comparison module is used for carrying out hash operation on the biological face recognition feature data of the current visitor to obtain a second abstract, comparing whether the first abstract and the second abstract are equal or not, and if so, granting the visitor access to the transaction node;
and the verification password pair module is used for corresponding the obtained secret key pair with the protection password set by the user to complete the correspondence between the user biological information, the secret key pair and the protection password.
10. A blockchain biometric facial recognition system as claimed in claim 9, comprising:
at least one memory for storing computer instructions;
at least one processor in communication with the memory, wherein the at least one processor, when executing the computer instructions, causes the system to perform: the device comprises a first acquisition module, a verification module, a second acquisition module, an uploading module, a query module, a comparison module and a verification password pair module.
CN202011488855.5A 2020-12-16 2020-12-16 Block chain biological face recognition method and system Pending CN112561525A (en)

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CN110955713A (en) * 2019-11-26 2020-04-03 上海中信信息发展股份有限公司 Mnemonic word generating method and device and storage medium
CN111222880A (en) * 2019-12-31 2020-06-02 陕西医链区块链集团有限公司 Block chain key generation method based on biological identification
CN111553694A (en) * 2020-05-21 2020-08-18 陈议尊 Distributed storage block chain method and system

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Publication number Priority date Publication date Assignee Title
CN109063498A (en) * 2018-07-27 2018-12-21 深圳市新名泽科技有限公司 Digital asset storage method, device, restoration methods and device
CN110955713A (en) * 2019-11-26 2020-04-03 上海中信信息发展股份有限公司 Mnemonic word generating method and device and storage medium
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