CN110647787A - Private key generation and decryption method and system based on iris recognition - Google Patents
Private key generation and decryption method and system based on iris recognition Download PDFInfo
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
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- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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Abstract
The invention discloses a private key generation and decryption method based on iris recognition and a corresponding system, wherein stable association relation is established by utilizing an iris and a private key, the iris position is positioned by acquisition, after continuous maximum iris areas are normalized, two-dimensional Gabor waves are utilized to screen and draw the physical characteristics of the areas, then the physical characteristics are converted into two-dimensional codes to form an iris code generation private key pair, the iris is used as the private key, the problems of forgetting, losing and stealing of the private key and the like are prevented, the uniqueness of the private key is ensured, the use is safe and convenient, the defects and the defects of the private key generation methods such as difficulty in distinguishing monozygotic twins and leakage of fingerprints by external articles are overcome, and the method has great significance for block chain development.
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 iris 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; however, the current popular practice is to establish reliable association between the generation of the private key and other information, and to obtain the private key by binding or obtaining other information, so how to manage the associated information in a reliable manner becomes the research focus of the problem. Some current schemes adopt a mode of binding human faces and private keys, and the mode has the problem that a small number of homozygotic twins cannot be distinguished from each other in the same way; some schemes adopt a mode of binding the fingerprint with a private key, and the mode has the problem that the fingerprint is acquired from an object touched by people and is stolen; how to provide a private key generation method which is less easy to lose than a human face, can distinguish monozygotic twins and has no fingerprint and is leaked by external articles is 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 iris recognition, which can prevent the private key from being lost and stolen, ensure the uniqueness of the private key, and are safe and convenient to use.
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 iris recognition comprises the following steps:
(1) aiming the infrared camera at a user;
(2) the camera records a section of user video, and extracts each frame in the video data;
(3) searching and locating iris positions from each frame of the video;
(4) checking whether the image quality of the searched iris position meets the requirement,
(5) if the requirement is met, performing the step (6), and if the requirement is not met, jumping to the next frame and returning to the step (4);
(6) calculating the accurate position of the iris interference factor, and marking the area of the position;
(7) calculating the unmarked continuous maximum area in the radius range of the iris;
(8) extracting the continuous maximum iris area in the step (7), and carrying out normalization processing on the area;
(9) screening and drawing the physical characteristics of the normalized processing area by using a two-dimensional Gabor wave;
(10) if any physical feature drawing fails, jumping to the next frame, returning to the step (9), if all frames fail to be processed, returning to the step (2), and if all the frames fail to be processed, entering the step (11);
(11) converting the vector of the physical characteristics of the successfully drawn normalized processing area into two-dimensional code information;
(12) splitting two-dimension code information into a plurality of short two-dimension codes, and organizing the plurality of short two-dimension codes in a matrix form to form an iris code;
(13) extracting unique features from the iris codes by adopting a data digest algorithm, and generating a key pair by using the unique features to complete the generation of an iris private key;
(14) keeping the private key and publishing the private key;
(15) encrypting data by using a private key, publishing the encrypted data, verifying the data by using a public key by an external person, and decrypting the data by using the private key by a user;
(16) and completing the decryption and use of the iris private key.
Further, the method for searching and locating the iris position from each frame of the video in the step (3) is as follows:
(31) judging whether a human face exists in the frame picture;
(32) if the face exists, the step (33) is carried out, if the face does not exist, the next frame is skipped, and the step (31) is returned;
(33) judging whether human eyes exist in the frame picture;
(34) if the eyes exist, the step (35) is carried out, if the eyes do not exist, the next frame is jumped to, and the step (33) is returned;
(35) searching iris positions;
(36) if the iris position is found, the step (4) is carried out, and if the iris position is not found, the next frame is skipped to, and the step (35) is returned.
Further, the image quality in the step (4) includes the definition of the image, the brightness of the image, whether the image is moving, and the focusing degree of the image.
The step (6) of calculating the position of the iris interference factor and marking the area of the position comprises the following steps:
(61) calculating the coordinates and the radius of the pupil and the iris;
(62) searching eyelid areas within the radius range of the iris;
(63) if the eyelid is searched, marking the region as the accurate position of the iris, and if the eyelid is not searched, skipping marking;
(64) searching eyelash areas within the radius range of the iris;
(65) if eyelashes are searched, marking the area as the accurate position of the iris, and if eyelids are not searched, skipping marking;
(66) searching a light spot area within the radius range of the iris;
(67) if the light spot is searched, marking the area as the accurate position of the iris, and if the light spot is not searched, skipping marking.
Further, the physical features in the step (9) include directions, spatial frequencies and images:
a system for private key generation and decryption based on iris recognition, comprising:
an iris collector: the iris collector is used for collecting images of human eyes;
an iris recognizer: the iris recognizer is used for extracting iris data in human eyes;
an iris cipher key device: the iris cipher key device is used for generating a cipher key pair through an iris feature code;
the iris collector, the iris recognizer and the iris key device are sequentially connected.
Further, the iris collector include image acquisition module and face identification module and people's eye identification module and the thick orientation module of iris, the image acquisition module constitute by infrared camera and memory for collect and trun into picture information with the information acquisition that the far infrared camera was gathered, face identification module be used for discerning the face part in the picture information, people's eye identification module be arranged in discerning the people's eye part in the people's face, the thick orientation module of iris be used for discerning the iris position in the people's eye.
Furthermore, the iris recognizer comprises an iris image evaluation module, an iris accurate positioning module, an iris preprocessing module and an iris feature extraction module, wherein the iris image evaluation module is used for analyzing the quality of an iris image, skipping a current frame in a video when the quality is not good, analyzing a next frame and finding an image meeting the quality requirement; the iris accurate positioning module is used for identifying the accurate position of the iris in the image and acquiring the center coordinates and the radius of the pupil and the iris; the iris preprocessing module is used for removing interference factors of an iris area and normalizing the available area; the iris feature extraction module is used for extracting the unique feature iris code of the iris, screening and drawing the normalized image into vectors by utilizing two-dimensional Gabor waves, and drawing the iris code by using vector information.
Further, the interference factors include eyelids, eyelashes, light spots and the like.
Furthermore, the iris cipher key device comprises a seed generation module and a cipher key pair generation module, wherein the seed generation module is used for extracting iris unique identification characteristic iris codes to generate a fixed characteristic value; and the key pair generation module is used for binding the unique iris identification characteristic value with the environment variable to generate a key pair.
The invention has the beneficial effects that:
according to the method, the positions of the irises are collected and positioned, after the continuous maximum iris areas are subjected to normalization processing, the physical characteristics of the areas are screened and drawn by using two-dimensional Gabor waves, and then the physical characteristics are converted into two-dimensional codes to form the iris code generation private key pair.
Drawings
FIG. 1 is a block diagram of a system according to the present invention;
the following drawings: 100-iris collector; 200-an iris recognizer; 300-an iris key device; 101-an image acquisition module; 102-a face recognition module; 103-a human eye recognition module; 104-iris coarse positioning module; 201-iris image evaluation module; 202-an iris accurate positioning module; 203-an iris preprocessing module; 204-an iris feature extraction module; 301-a seed generation module; 302-a key pair generation 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.
The private key generation mode of the current block chain is combined with the characteristics of people, the most common mode is to use a human face and a fingerprint as one of private keys at present, but the human face mode has the problem that a small number of homozygote twins cannot be distinguished from each other if the length of the homozygote twins is the same; the method of binding the fingerprint and the private key is adopted, and the method has the problem that the fingerprint is collected from the touched object and is stolen; the most core idea for solving the problems is to search human body characteristics which are more different than fingerprints, the characteristics do not directly contact with the outside world, and have consistent characteristics due to monozygotic twins, and the best choice of human eyes can not only inherit the advantages of human faces and fingerprints but also avoid the shortages of the human faces and the fingerprints from being the irises of human eyes from the top to the bottom of human bodies. The iris is the muscle of human control eye pupil, it is the colored part of the eye formed based on melatonin, its color and structure are related to gene, but the formation of detail is related to growth environment, so the key point for the application of iris lies in the identification and extraction of detail characteristic, and establishes stable relationship with private key. The invention is based on the point, and particularly discloses a private key generation and decryption method based on iris recognition, which comprises the following steps:
(1) aiming the infrared camera at a user;
(2) the camera records a section of user video, extracts each frame in the video data, stores the video in the memory in the process, and extracts each frame in the video data of the memory by using the processor;
(3) the specific method for searching and locating the position of the iris from each frame of the video comprises the following steps: (31) judging whether a human face exists in the frame picture; the judgment method also utilizes a processor, the processor can preset a human face model, and the human face model is defined as the human face as long as each frame of image corresponds to the model; (32) if the face exists, the step (33) is carried out, if the face does not exist, the next frame is skipped, and the step (31) is returned; (33) judging whether human eyes exist in the frame picture; the method for judging the human eyes is the same as the human faces, and a human eye model is preset by the processor and then matched; (34) if the eyes exist, the step (35) is carried out, if the eyes do not exist, the next frame is jumped to, and the step (33) is returned; (35) searching iris positions; (36) if the iris position is searched, performing the step (4), if the iris position is not searched, jumping to the next frame, returning to the step (35), wherein the iris position searched in the step is only the approximate position of the iris, and the iris position is searched in the human eye in a manner of searching the shape similar to the iris model through the presetting of the processor;
(4) checking whether the image quality of the searched iris position meets the requirement, wherein the specific image quality comprises the definition of the image, the brightness of the image, whether the image moves or not and the focusing degree of the image, namely, checking whether the definition of the image meets the requirement or not, if so, checking whether the brightness of the image meets the requirement or not, if so, checking whether the image moves or not, and if so, checking whether the focusing degree of the image meets the requirement or not.
(5) If all the requirements are met, performing the step (6), and if any one of the requirements is not met, jumping to the next frame and returning to the step (4);
(6) calculating the position of the iris interference factor, and marking the area of the position; specifically, the method for calculating the position of the iris interference factor in the step (6) and labeling the area of the position comprises the following steps: (61) calculating the coordinates and the radius of the pupil and the iris; (62) searching eyelid areas within the radius range of the iris; (63) if the eyelid is searched, marking the region as the accurate position of the iris, and if the eyelid is not searched, skipping marking; (64) searching eyelash areas within the radius range of the iris; (65) if eyelashes are searched, marking the area as the accurate position of the iris, and if eyelids are not searched, skipping marking; (66) searching a light spot area within the radius range of the iris; (67) if the light spot is searched, the area is marked as the accurate position of the iris, if the light spot is not searched, the marking is skipped, through the steps, the accurate position of the iris can be further determined, and the position is positioned by marking the accurate position of the iris.
(7) Calculating the unmarked continuous maximum area in the radius range of the iris, wherein the process is the key step of eliminating interference factors and determining the accurate position of the iris;
(8) extracting the continuous maximum iris area in the step (7), and carrying out normalization processing on the area;
(9) screening and drawing physical characteristics of the normalization processing area by using a two-dimensional Gabor wave, wherein the physical characteristics in the step (9) comprise directions, spatial frequencies and images; the Gabor wave transform is generated from a simulation of the human visual system. By simulating the human visual system, the retinal image can be decomposed into a set of filtered images, each of which can reflect the intensity variations in frequency and direction over a local range. Texture features can be obtained through a set of multi-channel Gabor filters. The root of the Gabor transform is the design of the Gabor filter, which in turn is the design of its frequency function (U, V) and the Gauss function parameter(s). In practice, the Gabor transform uses a Gauss function as a window function in order to extract local information of the Fourier transform of the signal, and since the Fourier transform of a Gauss function is also a Gauss function, the inverse Fourier transform is also local. By selecting the frequency parameter and the Gaussian function parameter, the Gabor transformation can select a plurality of texture features, but the Gabor is non-orthogonal, and different feature components have redundancy, so that the efficiency in analyzing the texture image is not high.
(10) If any physical characteristic fails to be drawn, jumping to the next frame, returning to the step (9), redrawing, if all the frames fail to be processed, returning to the step (2), re-acquiring the image, and if all the frames fail to be processed, entering the step (11);
(11) converting the vector of the physical characteristics of the successfully drawn normalized processing area into two-dimensional code information;
(12) splitting two-dimension code information into a plurality of short two-dimension codes, and organizing the plurality of short two-dimension codes in a matrix form to form an iris code;
(13) extracting unique features from the iris codes by adopting a data digest algorithm, and generating a key pair by using the unique features to complete the generation of an iris private key;
(14) keeping the private key and publishing the private key;
(15) encrypting data by using a private key, publishing the encrypted data, verifying the data by using a public key by an external person, and decrypting the data by using the private key by a user;
(16) and completing the decryption and use of the iris private key.
The invention also discloses a system for generating and decrypting the private key based on iris recognition, which comprises the following components as shown in figure 1:
the iris collector 100: the iris collector 100 is used for collecting images of human eyes; specifically, the iris collector 100 includes an image collection module 101, a face recognition module 102, a human eye recognition module 103 and an iris rough positioning module 104, where the image collection module 101 is composed of an infrared camera, a memory and a processor, and is configured to collect and convert information collected by the infrared camera into picture information, specifically, a video is recorded by the infrared camera, a frame number of the video is extracted by the processor and converted into an image, the face recognition module 102 is configured to recognize a face part in the picture information, the face recognition module 102 is also configured to perform face part recognition by the processor, first, the processor presets a face model, the model of the image of each frame is recognized as long as the model is matched with the face model, and the human eye recognition module 103 is configured to recognize a human eye part in a human face, the recognition mode is the same as the face recognition, and specifically, a human eye model is preset through a processor; the iris rough positioning module 104 is used for identifying the iris position in human eyes by scanning human eyes through a processor and comparing a preset iris model to find out the approximate position.
The iris recognizer 200: the iris recognizer 200 is used for extracting iris data in human eyes; the iris recognizer 200 comprises an iris image evaluation module 201, an iris accurate positioning module 202, an iris preprocessing module 203 and an iris feature extraction module 204, wherein the iris image evaluation module 201 is used for analyzing the quality of an iris image, specifically, analyzing whether the iris image is clear, whether the brightness is enough, whether motion blur exists or not and whether the focusing degree is enough or not, and skipping a current frame in a video if the iris image is not clear until an image meeting the quality requirement is found; the iris accurate positioning module 202 is used for identifying the accurate position of the iris in the image and acquiring the center coordinates and the radius of the pupil and the iris; the iris preprocessing module 203 is used for removing interference factors of an iris area, such as eyelids, eyelashes and light spots, which are interference factors, and normalizing the available area; the iris feature extraction module 204 is used for extracting the unique feature iris code of the iris, screening and drawing the normalized image into vectors by using two-dimensional Gabor waves, and drawing the iris code by using the vector information. The Gabor wave transform is generated from a simulation of the human visual system. By simulating the human visual system, the retinal image can be decomposed into a set of filtered images, each of which can reflect the intensity variations in frequency and direction over a local range. Texture features can be obtained through a set of multi-channel Gabor filters. The root of the Gabor transform is the design of the Gabor filter, which in turn is the design of its frequency function (U, V) and the Gauss function parameter(s). In practice, the Gabor transform uses a Gauss function as a window function in order to extract local information of the Fourier transform of the signal, and since the Fourier transform of a Gauss function is also a Gauss function, the inverse Fourier transform is also local. By selecting the frequency parameter and the Gaussian function parameter, the Gabor transformation can select a plurality of texture features, but the Gabor is non-orthogonal, and different feature components have redundancy, so that the efficiency in analyzing the texture image is not high.
The iris key device 300: the iris cipher key device 300 is used for generating a cipher key pair through an iris feature code; specifically, the iris cipher key device 300 includes a seed generation module 301 and a cipher key pair generation module 302, where the seed generation module 301 is configured to extract and generate an iris unique identification feature iris code into a fixed feature value; the key pair generation module 302 is configured to generate a key pair after binding the unique iris identification feature value with the environment variable.
The iris collector 100, the iris recognizer 200 and the iris key device 300 are connected in sequence. The specific use and connection method is as follows:
firstly, a user stands in front of an infrared camera of an image acquisition module 101, the infrared camera records a section of video of the user, the video is stored in a memory, and the video is converted into a picture through a processor of the image acquisition module 101; then, the face recognition module 102 recognizes the face part in the picture information through a preset face model; the human eye recognition module 103 recognizes a human eye part in the picture information through a preset human eye model in the image with the human face recognized, then the iris rough positioning module 104 recognizes an approximate position of an iris in the human eye, if the iris cannot be recognized in the process, the next image recognition is skipped, and if the iris cannot be recognized in the whole video, the camera needs to acquire the image again. Then, the image of the approximate position of the iris is identified for image evaluation, and the iris image evaluation module 201 of the iris identifier 200 is used for evaluating and analyzing whether the iris image is clear, whether the brightness is enough, whether the motion blur exists and whether the focusing degree is enough, and if one is not enough, the current frame in the video is skipped until the image meeting the quality requirement is found. The iris accurate positioning module 202 is used for identifying the accurate position of the iris in the image, interference factors, specifically light spot factors such as eyelids, eyelashes and light spots, are sent out by a processor of the iris accurate positioning module 202 in the process, after the interference factors are eliminated, the processor of the iris accurate positioning module 202 can normalize the residual available area, then the iris feature extraction module 204 extracts the unique feature iris code of the iris, the normalized image is screened and drawn into a vector by a two-dimensional Gabor wave, the information of phasor comprises direction, space frequency and image position information, and finally the vector information is used for drawing the iris code; in this step, the extraction of the iris is completed, and then the iris unique identification feature iris code is extracted and generated into a fixed feature value by using the seed generation module 301 of the iris secret key device 300; then, the key pair generation module 302 binds the unique iris identification feature value with an environment variable to generate a key pair, where the environment variable refers to an application environment of an iris private key, and if the iris identification feature value is applied to a block chain, the iris feature needs to be highly bound with the block, so that a malicious person can be prevented from forging encrypted information by analyzing iris data of a historical block. And completing the generation and decryption of the private key.
According to the method, the positions of the irises are collected and positioned, after the continuous maximum iris areas are subjected to normalization processing, the physical characteristics of the areas are screened and drawn by using two-dimensional Gabor waves, and then the physical characteristics are converted into two-dimensional codes to form the iris code generation private key pair, the irises are used as the private keys, the problems that the private keys are forgotten and lost and stolen and the like are solved, the uniqueness of the private keys is ensured, the use is safe and convenient, the defects and the defects of the private key generation method that the homozygote twins are difficult to distinguish and fingerprints are leaked by external articles and the like are overcome, and the.
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 (10)
1. A private key generation and decryption method based on iris recognition comprises the following steps:
(1) aiming the infrared camera at a user;
(2) the camera records a section of user video, and extracts each frame in the video data;
(3) searching and locating iris positions from each frame of the video;
(4) checking whether the image quality of the searched iris position meets the requirement,
(5) if the requirement is met, performing the step (6), and if the requirement is not met, jumping to the next frame and returning to the step (4);
(6) calculating the position of the iris interference factor, and marking the area of the position;
(7) calculating the unmarked continuous maximum area in the radius range of the iris;
(8) extracting the continuous maximum iris area in the step (7), and carrying out normalization processing on the area;
(9) screening and drawing the physical characteristics of the normalized processing area by using a two-dimensional Gabor wave;
(10) if any physical feature drawing fails, jumping to the next frame, returning to the step (9), if all frames fail to be processed, returning to the step (2), and if all the frames fail to be processed, entering the step (11);
(11) converting the vector of the physical characteristics of the successfully drawn normalized processing area into two-dimensional code information;
(12) splitting two-dimension code information into a plurality of short two-dimension codes, and organizing the plurality of short two-dimension codes in a matrix form to form an iris code;
(13) extracting unique features from the iris codes by adopting a data digest algorithm, and generating a key pair by using the unique features to complete the generation of an iris private key;
(14) keeping the private key and publishing the private key;
(15) encrypting data by using a private key, publishing the encrypted data, verifying the data by using a public key by an external person, and decrypting the data by using the private key by a user;
(16) and completing the decryption and use of the iris private key.
2. The method for generating and decrypting the private key based on iris recognition according to claim 1, wherein the method for searching and locating the iris position from each frame of the video in the step (3) is:
(31) judging whether a human face exists in the frame picture;
(32) if the face exists, the step (33) is carried out, if the face does not exist, the next frame is skipped, and the step (31) is returned;
(33) judging whether human eyes exist in the frame picture;
(34) if the eyes exist, the step (35) is carried out, if the eyes do not exist, the next frame is jumped to, and the step (33) is returned;
(35) searching iris positions;
(36) if the iris position is found, the step (4) is carried out, and if the iris position is not found, the next frame is skipped to, and the step (35) is returned.
3. The method for generating and decrypting the private key based on iris recognition of claim 1, wherein the image quality in the step (4) includes the sharpness of the image, the brightness of the image, whether the image is moving, and the focusing degree of the image.
4. The method for generating and decrypting the private key based on iris recognition according to claim 1, wherein the step (6) of calculating the precise position of the iris and labeling the area where the position is located is performed by:
(61) calculating the coordinates and the radius of the pupil and the iris;
(62) searching eyelid areas within the radius range of the iris;
(63) if the eyelid is searched, marking the region as the accurate position of the iris, and if the eyelid is not searched, skipping marking;
(64) searching eyelash areas within the radius range of the iris;
(65) if eyelashes are searched, marking the area as the accurate position of the iris, and if eyelids are not searched, skipping marking;
(66) searching a light spot area within the radius range of the iris;
(67) if the light spot is searched, marking the area as the accurate position of the iris, and if the light spot is not searched, skipping marking.
5. A method for private key generation and decryption based on iris recognition as claimed in claim 1, wherein the physical characteristics in step (9) include direction, spatial frequency and image.
6. A system for private key generation and decryption based on iris recognition, comprising:
an iris collector: the iris collector is used for collecting images of human eyes;
an iris recognizer: the iris recognizer is used for extracting iris data in human eyes;
an iris cipher key device: the iris cipher key device is used for generating a cipher key pair through an iris feature code;
the iris collector, the iris recognizer and the iris key device are sequentially connected.
7. The system for generating and decrypting the private key based on the iris recognition as claimed in claim 6, wherein the iris collector comprises an image collection module, a face recognition module, an eye recognition module and an iris rough positioning module, the image collection module comprises an infrared camera and a memory and is used for collecting information collected by the far infrared camera and converting the information into picture information, the face recognition module is used for recognizing a face part in the picture information, the eye recognition module is used for recognizing an eye part in a face, and the iris rough positioning module is used for recognizing an iris position in eyes.
8. The system for private key generation and decryption based on iris recognition as claimed in claim 6, wherein the iris recognizer comprises an iris image evaluation module, an iris accurate positioning module, an iris preprocessing module and an iris feature extraction module, the iris image evaluation module is used for analyzing the quality of the iris image, when the quality is not good, the current frame in the video is skipped, and the next frame is analyzed to find the image meeting the quality requirement; the iris accurate positioning module is used for identifying the accurate position of the iris in the image and acquiring the center coordinates and the radius of the pupil and the iris; the iris preprocessing module is used for removing interference factors of an iris area and normalizing the available area; the iris feature extraction module is used for extracting the unique feature iris code of the iris, screening and drawing the normalized image into vectors by utilizing two-dimensional Gabor waves, and drawing the iris code by using vector information.
9. The system of claim 8, wherein the disturbing factors comprise eyelids, eyelashes, and flare.
10. The system for private key generation and decryption based on iris recognition of claim 6, wherein the iris cipher key generator comprises a seed generation module and a key pair generation module, the seed generation module is used for extracting iris unique identification feature iris code to generate a fixed feature value; and the key pair generation module is used for binding the unique iris identification characteristic value with the environment variable to generate a key pair.
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