CN110661617A - Private key generation and decryption method and system based on face recognition - Google Patents
Private key generation and decryption method and system based on face recognition Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
- H04L9/0861—Generation of secret information including derivation or calculation of cryptographic keys or passwords
- H04L9/0869—Generation of secret information including derivation or calculation of cryptographic keys or passwords involving random numbers or seeds
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- 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
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- H—ELECTRICITY
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- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
- H04L9/0861—Generation of secret information including derivation or calculation of cryptographic keys or passwords
- H04L9/0866—Generation of secret information including derivation or calculation of cryptographic keys or passwords involving user or device identifiers, e.g. serial number, physical or biometrical information, DNA, hand-signature or measurable physical characteristics
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Abstract
The invention discloses a private key generation and decryption method based on face recognition, which comprises the steps of carrying out living body analysis and counterfeit analysis on face characteristic data through a system; the face feature data is traced back to the date when the person creates the private key, and the traced face feature data is summarized and then the abstract is obtained; generating a key pair by taking the digest as a random factor, and decrypting data by taking the key pair as a private key; the invention also discloses a private key generation and decryption system based on face recognition, which can prevent the problems of private key forgetting, private key losing and theft and the like by acquiring the face characteristic data and using the face characteristic data as the private key or the seed of the generated private key, thereby realizing that the private key does not need to be memorized and hand-copied and is safe and convenient to use; the authenticity of the face feature data is judged by using the living body check detector, the face photo and the counterfeit face data feature decryption data are prevented, and the safety of the private key is ensured.
Description
Technical Field
The invention belongs to the field of block chains, and particularly relates to a private key generation and decryption method and system based on face recognition.
Background
In the world of a block chain, the reliability of all data is established on the basis of cryptography, the type of an encryption algorithm which is applied most in the block chain is asymmetric encryption, the asymmetric encryption protects the information security by a pair of public keys and private keys, the public keys are used for public verification information, the private keys are held by the private keys, the privacy of the private keys determines the encryption reliability of the encryption algorithm, the private keys are often formed by a long string of letters with irregular capital and small letters and numbers which exceed 128 bits, the private keys are difficult to be directly recorded by memory, and the private keys are often recorded by copying and recording the private keys on an electronic memorandum or a hand-copy record paper notepad, so that the loss of the paper notepad and the theft of the electronic memorandum make the original secure encryption algorithm not so safe; it is critical that there is no better way of managing the private key to solve this problem; at present, a mode of generating a key pair by using mnemonics is adopted on the world, letters or numbers which can be memorized by human brains are used as seeds to generate a fixed pair of public keys and private keys, the private keys can be remembered as long as the seeds are remembered, but due to the offline property of block chain data, anyone can inexhaustible trial passwords, so that the seeds are often required to be very complicated, such as a Changshi, the passwords are different from the passwords which are used by people in daily life, so that the personnel can select and record the passwords without autonomy, and the recorded passwords can be stolen due to seed leakage. Similar passwords are more widely used outside the blockchain, and almost all applications for encrypting private keys have similar problems, so that how to provide a private key which can be held without being memorized and being hand-copied becomes a problem which needs to be solved urgently.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method and a system for generating and decrypting a private key based on face recognition, which can prevent the private key from being lost and stolen, realize that the private key does not need to be memorized and hand-copied, and have safe use and convenience.
In order to solve the technical problems, the technical solution of the invention is as follows:
a private key generation and decryption method based on face recognition comprises the following steps:
(1) collecting face feature data by adopting a camera;
(2) summarizing the face feature data and then taking an abstract;
(3) generating a key pair by taking the abstract as a random factor, and storing the key pair by a user to finish the generation of a private key of the user;
(4) a user acquires a section of data needing to be decrypted;
(5) the user aims the face at the camera, and the camera extracts face characteristic data;
(6) the system performs living body analysis on the face characteristic data;
(7) the system carries out counterfeit analysis on the face characteristic data;
(8) backtracking the face feature data to the date when the person creates the private key, and summarizing the backtracked face feature data to remove the abstract;
(9) generating a key pair by taking the digest as a random factor, and decrypting data by taking the key pair as a private key;
(10) and obtaining original data before encryption and finishing data decryption.
Further, the method for acquiring the face feature data in the step (1) comprises the following steps:
(11) aiming the camera at the face to acquire a face video;
(12) converting the face video into a one-piece face picture;
(13) extracting human face features from the human face picture, wherein the human face features mainly comprise eye features, nose features and mouth features;
(14) recording the facial features of other parts, including eyebrow, ear and face features;
(15) combining a plurality of features together to form face feature data;
(16) and comparing the face characteristic data of different face pictures, and adjusting and correcting the face characteristic data.
Further, the system in step (6) performs living body analysis on the face feature data by the method comprising:
(61) aiming the camera at the face to acquire a face video;
(62) detecting whether the face of the user has activity, if so, performing step (63), otherwise, judging that the user is not a living body, and ending the data decryption process;
(63) randomly setting basic actions of a face acquisition sample;
(64) judging whether the human face video is subjected to basic motion of a human face acquisition sample, if so, judging that the user is a living body, executing the step (7), if not, judging that the user is not a living body, and ending the data decryption process;
(65) and completing the living body analysis of the user.
Further, the basic actions of the human face acquisition sample comprise opening eyes or shaking head or opening mouth.
Further, the method for performing counterfeit analysis on the face feature data by the system in the step (7) is as follows:
(71) adding a noise data set by the party to the face characteristic data;
(72) generating a private key by the data and the face feature data;
(73) and (4) whether the matched private key is consistent with the private key added with the noise data, if so, the data is received, the step (8) is carried out, if not, the data is set as counterfeit data, the data is abandoned, and the data decryption process is ended.
A system for private key generation and decryption based on face recognition, comprising:
a face feature extractor: the face feature extractor is used for extracting face features and acquiring face feature data;
a feature private key generator: the characteristic private key generator is used for ensuring the stability of the characteristic generated private key;
the living body verification detector: the living body check detector is used for checking a private key of a user and preventing face feature data from being counterfeited and deceived by a face photo;
the human face feature extractor, the feature private key generator and the living body check detector are sequentially connected.
Furthermore, the human face feature extractor comprises a human face acquisition module, a human face recognition module, a feature extraction module and a time light backtracking module, wherein the human face acquisition module is used for converting a human face video shot by a camera into a picture; the face recognition module is used for recognizing and extracting the face in the photo; the characteristic extraction module is used for extracting the characteristics of the nose, the eyes and the mouth of the human face; the time light backtracking module is used for backtracking the human face features at a specific time to the previous specific time according to the natural growth rule of human beings.
Furthermore, the characteristic private key generator comprises a characteristic code generation module and a private key generation module, wherein the characteristic code generation module is used for converting the characteristic information of the face into a fixed characteristic code; the private key generation module is used for generating a secret key and a private key pair for the feature code.
Furthermore, the living body checking detector comprises a video acquisition module, a movement detection module and a detection reply module, wherein the video acquisition module is used for recording and acquiring a section of face video; the activity detection module is used for detecting whether the face has activity, if so, the activity detection module adopts the face feature data, and if not, the data is abandoned, and the data decryption process is ended; the detection reply module is used for giving an acquisition requirement at random and detecting whether the face moves as required, if the face moves as required, the detection reply module adopts the face characteristic data, and if the face does not move as required, the detection reply module gives up the data and ends the data decryption process.
The invention has the beneficial effects that:
1. according to the invention, the face characteristic data is collected and used as the private key or the seed for generating the private key, so that the problems of forgetting, losing and stealing the private key and the like are prevented, the private key is not required to be memorized and hand-copied, and the private key is safe and convenient to use;
2. the invention judges the authenticity of the face feature data by using the living body check detector, prevents the face photo and the counterfeit face data feature from decrypting the data, and ensures the safety of the private key.
Drawings
FIG. 1 is a flow chart of a corresponding method of the present invention;
FIG. 2 is a block diagram of the architecture of a corresponding system of the present invention;
the following drawings: 100-a face feature extractor; 200-a feature private key generator; 300-a liveness check detector; 101-a face acquisition module; 102-a face recognition module; 103-a feature extraction module; 104-time light backtracking module; 201-feature code generation module; 202-private key generation module; 301-video capture module; 302-an activity detection module; 303-a detection reply module;
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples. It should be noted that the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
In the field of block chains, the use of a private key is crucial, and the private key on the current world is either too simple, so that the private key is unsafe, or too complex, so that the private key is difficult to remember; besides the block chain, similar passwords are more widely used, and almost all applications of encrypting the private key have the problems of difficulty in remembering and safety, so that how to provide the private key which can be held by people without remembering and hand-reading becomes a problem which needs to be solved urgently. The invention effectively solves the problems through improvement, and the core idea for solving the problems is that people who need to memorize can hand-copy or record, so that data which can not be hand-copied does not need to be memorized as a private key, the data which can not be memorized and hand-copied is only obtained from the inherent data of people, such as human faces, and the human face characteristic data is used as the private key or the seed for generating the private key, so that the data can be encrypted and protected, and the secret key is not leaked. The problem to be solved has three core difficulties, the first is face feature extraction, the second is the stability of a feature generation private key, and the third is how to prevent spoofing by face photos. The present invention solves these three problems by improvement.
The invention specifically discloses a private key generation and decryption method based on face recognition, which comprises the following steps as shown in figure 1:
(1) adopting a camera to collect face characteristic data, wherein the specific collection method comprises the following steps of (11) aligning the camera to a face to collect a face video, namely shooting a small section of face video through a camera; (12) the process can be completed through a system, the video is formed by overlapping a plurality of frames, and the mode of selecting the pictures is that the video is captured; (13) extracting human face features from a human face picture, wherein the human face features mainly comprise eye features, nose features and mouth features, and the eye features comprise eye width, eye distance, eye angle amplitude, eye angle and the like; nose characteristics including bridge line, bridge length, angle to the eyes, etc.; mouth features including mouth width, mouth curve, mouth-nose bridge angle, etc.; (14) recording the facial features of other parts, including eyebrow, ear and face features, and specifically including all facial features such as chin and the like; (15) combining a plurality of features together to form face feature data, and ensuring that the face feature data corresponds to the user one by one; (16) the method mainly comprises the steps of comparing face characteristic data of different face pictures, adjusting and correcting the face characteristic data, and correcting the face characteristic data from different pictures extracted from a face video to ensure that the face characteristic data are accurate.
(2) Summarizing the face feature data and then taking an abstract, wherein the abstract mainly represents the points which most represent the personal features, such as the big eyes, the high nose bridge, the eyebrow shape and the like;
(3) generating a key pair by taking the abstract as a random factor, and storing the key pair by a user to finish the generation of a private key of the user; the generation of the private key related to the face is completed through the steps, and the private key verification can be completed only by using the face verification at the later stage without memorizing or worrying about forgetting;
(4) a user acquires a section of data to be decrypted and waits for the private key to decrypt;
(5) the user aims the face at the camera, the camera extracts face characteristic data, the face characteristic mainly comprises eye characteristics, nose characteristics and mouth characteristics, and the eye characteristics comprise eye width, eye distance, eye angle amplitude, eye angle and the like; nose characteristics including bridge line, bridge length, angle to the eyes, etc.; mouth features including mouth width, mouth curve, mouth-nose bridge angle, etc.;
(6) the system performs living body analysis on the face characteristic data; the specific method for performing living body analysis on the face characteristic data by the system is as follows: (61) aiming the camera at the face to acquire a face video; (62) detecting whether the face of the user has activity, if so, performing step (63), otherwise, judging that the user is not a living body, and ending the data decryption process; (63) randomly setting basic actions of a face acquisition sample; (64) judging whether the human face in the human face video acquires basic actions of the sample, such as blinking, shaking head and the like; if yes, the user is judged to be a living body, the step (7) is executed, if not, the user is judged not to be a living body, and the data decryption process is ended; (65) and completing the living body analysis of the user. The step is mainly to prevent data leakage caused by the fact that others use the photo as a private key to decrypt data, and whether the photo is the photo can be judged through activity and basic action.
(7) The system carries out counterfeit analysis on the face characteristic data; specifically, the method for the system to perform counterfeit analysis on the face characteristic data comprises the following steps: (71) adding a noise data set by the party to the face characteristic data; (72) generating a private key by the data and the face feature data; (73) whether the matched private key is consistent with the private key added with the noise data at this time or not is judged, if so, the data is received, the step (8) is carried out, if not, the data is set as counterfeit data, the data is abandoned, and the data decryption process is ended; the step is mainly to prevent counterfeiting, in a block chain, although a private key is fixed, noise data which is only known by a principal is added in each use, the data can ensure that final data generated by the same private key is always different even if the encrypted data is the same, so that the situation that someone forges second authorization by directly using two sections of repeated data through authorization of the previous section can be prevented; therefore, the function of counterfeiting is achieved, the camera can be deceived by other faces, but the authorization on the data cannot pass; therefore, the private key is different when the data is decrypted according to different data, and the method can achieve the effect of preventing counterfeiting.
(8) The method comprises the steps of backtracking face feature data to a date when a person creates a private key, collecting the backtracked face feature data, and then removing a summary, wherein the time backtracking mainly utilizes face features of specific time to backtrack to the previous specified time according to a natural growth rule of human, for example, when the data is decrypted through the private key, the face is definitely different from the previous data, and the current face data is adjusted to the previous data according to the rule through the natural growth rule of human, for example, the eye distance is shortened, so that the face feature data is matched with the previous data, and then the data is decrypted.
(9) Generating a key pair by taking the digest as a random factor, and decrypting data by taking the key pair as a private key;
(10) and obtaining original data before encryption and finishing data decryption.
By the method, the private key is not easy to forget, and the safety of the private key is improved.
The invention also discloses a private key generation and decryption system based on face recognition, as shown in fig. 2, comprising:
the face feature extractor 100: the face feature extractor 100 is used for extracting face features to obtain face feature data; the human face feature extractor 100 specifically comprises a human face acquisition module 101, a human face recognition module 102, a feature extraction module 103 and a time light backtracking module 104, wherein the human face acquisition module 101 is used for converting a human face video shot by a camera into a picture, the specific human face acquisition module 101 is composed of the camera and a processor connected with the camera, and after the camera acquires data, the processor captures the picture in the unit of the number of collected video frames to complete the process from the human face video to the picture; the face recognition module 102 is configured to recognize and extract a face from the pictures, and remove pictures that are not faces from the pictures; the feature extraction module 103 is configured to extract features of a nose, eyes, and a mouth of a human face, specifically including eye features, nose features, and mouth features, where the eye features include eye width, inter-ocular distance, eye angle amplitude, eye angle, and the like; nose characteristics including bridge line, bridge length, angle to the eyes, etc.; mouth features including mouth width, mouth curve, mouth-nose angle, face features including eyebrow, ear, face shape, chin and other features; the time light backtracking module 104 is configured to backtrack the facial features at a specific time to a previous specific time according to the natural growth rule of human, for example, adjust an inter-ocular distance, wrinkles, and the like according to the growth cycle of human. The face feature extraction problem is well solved by the face feature extractor 100.
Feature private key generator 200: the feature private key generator 200 is used for ensuring the stability of the feature generated private key; specifically, the feature private key generator 200 includes a feature code generating module 201 and a private key generating module 202, where the feature code generating module 201 is configured to convert feature information of a human face into a fixed feature code; the private key generation module 202 is configured to generate a key and a private key pair for the feature code. Feature private key generator 200 is used to solve the stability problem of feature generated private keys.
The in-vivo verification detector 300: the living body check detector 300 is used for checking a private key of a user and preventing face feature data from being counterfeited and deceived by a face photo; specifically, the biopsy verification detector 300 includes a video acquisition module 301, an activity detection module 302, and a detection reply module 303, where the video acquisition module 301 is configured to record and acquire a section of face video. The video acquisition module 301 is only composed of a camera and a memory, after the camera shoots, data is transmitted to the memory, and the activity detection module 302 and the detection reply module 303 behind are judged by taking the video of the memory as original data; the activity detection module 302 is configured to detect whether the face has activity, if so, the activity detection module 302 accepts the facial feature data, and if not, abandons the data and ends the data decryption process; the detection reply module 303 is used for giving an acquisition requirement at random, detecting whether the human face moves as required or not, if the human face moves as required, the detection reply module 303 adopts the human face characteristic data, and if the human face does not move as required, the data is abandoned, and the data decryption process is ended, wherein the activity detection module 302 of the invention can also add noise data to the human face characteristic data, so that the data correspondence of each time is the uniqueness of the private key, and the counterfeiting is prevented.
The human face feature extractor 100, the feature private key generator 200 and the living body verification detector 300 are connected in sequence. The specific connection relation and the use method are as follows:
firstly, shooting a face video of a user through a face acquisition module 101 of a face feature extractor 100, and capturing a picture in a frame number unit of the acquired video through a processor to finish a process from face video recording to the picture; then, the face recognition module 102 recognizes and extracts the face in the picture, and removes the pictures which are not the face in the pictures; then extracting the features of the human face through a feature extraction module 103, wherein the features specifically comprise eye features, nose features and mouth features; after extracting the face feature data, summarizing the feature data by the feature code generation module 201 and the private key generation module 202 of the feature private key generator 200 to remove the abstract, converting the face feature information into a fixed feature code, and generating a key and a private key pair from the feature code by the private key generation module 202 to complete the generation of the private key. When data needs to be decrypted, a video acquisition module 301 of the living body verification detector 300 is used for recording and acquiring a user face video, and a following activity detection module 302 and a following detection reply module 303 are both judged by using the video of a memory as original data; the activity detection module 302 detects whether the face has activity, if so, the activity detection module 302 adopts the face feature data, and if not, the data is abandoned, and the data decryption process is ended; the detection reply module 303 is configured to randomly give an acquisition requirement, detect whether a human face moves as required, if the human face moves as required, the detection reply module 303 receives the human face feature data, and if the human face does not move as required, abandons the data, and ends the data decryption process, where the activity detection module 302 of the present invention further adds noise data to the human face feature data to ensure that each data correspondence is uniqueness of a private key, so as to prevent counterfeiting, and then backtracks the human face features of a specific time to a previously specified time according to a natural growth rule of a human, for example, according to a human growth cycle, adjust eye distance, wrinkles, and the like, through the temporal backtracking module 104. Then, the feature private key generator 200 is used for generating a private key to finish decryption, and a user obtains decrypted data to finish a decryption process.
According to the invention, the face characteristic data is collected and used as the private key or the seed for generating the private key, so that the problems of forgetting, losing and stealing the private key and the like are prevented, the private key is not required to be memorized and hand-copied, and the private key is safe and convenient to use; the authenticity of the face feature data is judged by using the living body check detector, the face photo and the counterfeit face data feature decryption data are prevented, and the safety of the private key is ensured.
The above-mentioned embodiments are only preferred embodiments of the present invention, and do not limit the technical scope of the present invention, so that the changes and modifications made by the claims and the specification of the present invention should fall within the scope of the present invention.
Claims (9)
1. A private key generation and decryption method based on face recognition comprises the following steps:
(1) collecting face feature data by adopting a camera;
(2) summarizing the face feature data and then taking an abstract;
(3) generating a key pair by taking the abstract as a random factor, and storing the key pair by a user to finish the generation of a private key of the user;
(4) a user acquires a section of data needing to be decrypted;
(5) the user aims the face at the camera, and the camera extracts face characteristic data;
(6) the system performs living body analysis on the face characteristic data;
(7) the system carries out counterfeit analysis on the face characteristic data;
(8) backtracking the face feature data to the date when the person creates the private key, and summarizing the backtracked face feature data to remove the abstract;
(9) generating a key pair by taking the digest as a random factor, and decrypting data by taking the key pair as a private key;
(10) and obtaining original data before encryption and finishing data decryption.
2. The method for generating and decrypting the private key based on the face recognition according to claim 1, wherein the method for collecting the face feature data in the step (1) comprises the following steps:
(11) aiming the camera at the face to acquire a face video;
(12) converting the face video into a one-piece face picture;
(13) extracting human face features from the human face picture, wherein the human face features mainly comprise eye features, nose features and mouth features;
(14) recording the facial features of other parts, including eyebrow, ear and face features;
(15) combining a plurality of features together to form face feature data;
(16) and comparing the face characteristic data of different face pictures, and adjusting and correcting the face characteristic data.
3. The method for generating and decrypting the private key based on the face recognition according to claim 1, wherein the system in the step (6) performs the living body analysis on the face feature data by:
(61) aiming the camera at the face to acquire a face video;
(62) detecting whether the face of the user has activity, if so, performing step (63), otherwise, judging that the user is not a living body, and ending the data decryption process;
(63) randomly setting basic actions of a face acquisition sample;
(64) judging whether the human face video is subjected to basic motion of a human face acquisition sample, if so, judging that the user is a living body, executing the step (7), if not, judging that the user is not a living body, and ending the data decryption process;
(65) and completing the living body analysis of the user.
4. The method for private key generation and decryption based on face recognition according to claim 3, wherein the basic actions of the face collection sample include opening eyes or shaking head or opening mouth.
5. The method for generating and decrypting the private key based on the face recognition according to claim 1, wherein the method for performing the counterfeit analysis on the face feature data by the system in the step (7) is as follows:
(71) adding a noise data set by the party to the face characteristic data;
(72) generating a private key by the data and the face feature data;
(73) and (4) whether the matched private key is consistent with the private key added with the noise data, if so, the data is received, the step (8) is carried out, if not, the data is set as counterfeit data, the data is abandoned, and the data decryption process is ended.
6. A system for private key generation and decryption based on face recognition, comprising:
a face feature extractor: the face feature extractor is used for extracting face features and acquiring face feature data;
a feature private key generator: the characteristic private key generator is used for ensuring the stability of the characteristic generated private key;
the living body verification detector: the living body check detector is used for checking a private key of a user and preventing face feature data from being counterfeited and deceived by a face photo;
the human face feature extractor, the feature private key generator and the living body check detector are sequentially connected.
7. The system for generating and decrypting the private key based on the face recognition is characterized in that the face feature extractor comprises a face acquisition module, a face recognition module, a feature extraction module and a time light backtracking module, wherein the face acquisition module is used for converting a face video shot by a camera into a picture; the face recognition module is used for recognizing and extracting the face in the photo; the characteristic extraction module is used for extracting the characteristics of the nose, the eyes and the mouth of the human face; the time light backtracking module is used for backtracking the human face features at a specific time to the previous specific time according to the natural growth rule of human beings.
8. The system for generating and decrypting the private key based on the face recognition as claimed in claim 6, wherein the feature private key generator comprises a feature code generating module and a private key generating module, the feature code generating module is used for converting the feature information of the face into a fixed feature code; the private key generation module is used for generating a secret key and a private key pair for the feature code.
9. The system for generating and decrypting the private key based on the face recognition as claimed in claim 6, wherein the living body verification detector comprises a video acquisition module, a motion detection module and a detection reply module, the video acquisition module is used for recording and acquiring a section of face video; the activity detection module is used for detecting whether the face has activity, if so, the activity detection module adopts the face feature data, and if not, the data is abandoned, and the data decryption process is ended; the detection reply module is used for giving an acquisition requirement at random and detecting whether the face moves as required, if the face moves as required, the detection reply module adopts the face characteristic data, and if the face does not move as required, the detection reply module gives up the data and ends the data decryption process.
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| CN114756848A (en) * | 2022-06-15 | 2022-07-15 | 国网浙江省电力有限公司 | Engineering digital audit data processing method based on basic data acquisition model |
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| CN110661617B (en) | 2022-11-25 |
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