CN117034236A - Iris data privacy protection and identification method and electronic equipment - Google Patents

Abstract

The application provides an iris data privacy protection and identification method and electronic equipment, wherein the privacy protection method realizes the primary encryption processing of original iris data by replacing and rearranging the original iris data to obtain rearranged iris data so as to improve the complexity of the iris data; further, by partitioning the rearranged iris data, the combined characteristics of all the data blocks of the rearranged iris data can be obtained, and by inverting and merging all the data blocks, the combined characteristics of all the data blocks can be represented, and the magnitude of the iris data can be reduced; finally, by grouping the combined iris data, sorting the groups respectively, determining the sorting sequence as the encrypted data of the original iris data, and standardizing the characteristics of the iris data, the characteristics of the iris data can be effectively hidden, so that the standardization degree of the iris data is improved, the data characteristics are reduced, and the iris data is prevented from being decrypted.

Description

Iris data privacy protection, identification methods and electronic devices

Technical field

The invention relates to the technical field of privacy protection and security, and specifically relates to an iris data privacy protection, identification method and electronic device.

Background technique

With the rapid development of technologies such as the Internet, mobile communications and the Internet of Things, people use various devices and applications to carry out daily activities, and the large amounts of data generated by these activities may contain users' personal privacy information. With the continuous development and maturity of biometric technology, various modes of biometric technology, such as iris recognition, face recognition, fingerprint recognition, etc., have been applied in financial and people's livelihood scenarios. However, when data flows are complex, data leaks may occur and the risk of personal information being used maliciously increases. As one of the most commonly used biometric features, industry and academia have conducted extensive research on how to effectively perform iris recognition and protect the privacy of user information.

In recent years, many iris data protection methods have been proposed, which are mainly divided into two categories: revocable iris biometric technology and iris biometric encryption system. However, in the field of revocable iris recognition technology, existing technical methods include solutions based on Bloom filters, solutions based on local sensitive hashing, and solutions based on feature adaptive random projection. Since the above methods are irreversible and reversible, There is no good balance between revocability and unlinkability, and it is impossible to completely prevent the user's iris data from being decrypted, resulting in the inability to effectively guarantee the security of the user's iris data.

Therefore, in the process of protecting the security of iris data in the prior art, there is a problem that the iris data cannot be avoided from being decrypted.

Contents of the invention

In view of this, it is necessary to provide an iris data privacy protection, identification method and electronic device to solve the problem of unavoidable decryption of iris data in the process of protecting iris data security in the existing technology.

In order to solve the above problems, the present invention provides an iris data privacy protection method, including:

Get raw iris data;

Perform replacement and rearrangement of the original iris data to obtain rearranged iris data;

Divide the rearranged iris data into blocks to obtain multiple data blocks, and perform inversion and merging of the multiple data blocks respectively to obtain the inversion and merged iris data;

Group the reversed and merged iris data to obtain multiple data groups, and sort the multiple data groups respectively to obtain a sorting sequence of the reversed and merged iris data, and determine that the sorting sequence is the encrypted data of the original iris data.

Further, the original iris data is replaced and rearranged to obtain rearranged iris data, including:

Obtain a random permutation string, where the length of the random permutation string is the same as the length of the original iris data, and the numbers in the random permutation string do not repeat;

Based on the random permutation string, the original iris data is permuted and rearranged to obtain the rearranged iris data.

Further, the rearranged iris data is divided into blocks to obtain multiple data blocks, and the multiple data blocks are inverted and merged respectively to obtain the inverted and merged iris data, including:

Set the blocking bit width, and divide the rearranged iris data into multiple data blocks according to the blocking bit width;

Convert binary data in multiple data blocks into decimal data to obtain multiple decimal iris data;

According to the block bit width and based on the decimal standard value calculation formula, the decimal standard value is obtained;

According to the standard decimal value, multiple decimal iris data are inverted and merged to obtain the inverted and merged iris data.

Furthermore, the decimal standard value calculation formula is:

S＝2 ^b-1 -1

Among them, S is the decimal standard value, and b is the block bit width.

Further, according to the decimal standard value, multiple decimal iris data are inverted and merged to obtain inverted and merged iris data, including:

Judge the size of multiple decimal iris data and decimal standard values in sequence;

When the decimal iris data is greater than the decimal standard value, based on the inversion formula, determine the inverted combined iris data corresponding to the decimal iris data;

When the decimal iris data is not greater than the decimal standard value, it is determined that the decimal iris data is its corresponding inverted merged iris data.

Furthermore, the inverse formula is:

r _i =2 ^b -1-w _i

Among them, r _i is the inverted merged iris data, and w _i is the decimal iris data.

Further, group the reversed and merged iris data to obtain multiple data groups, and sort the multiple data groups respectively to obtain a sorting sequence of the reversed and merged iris data, and determine that the sorting sequence is the encrypted data of the original iris data, include:

Set the grouping width and divide the inverted merged iris data into multiple data groups according to the grouping width;

Sort the inverted and merged iris data in multiple data groups according to the size of the data values, and obtain multiple sorting sequences corresponding to the multiple data groups;

The sorted sequence is determined to be the encrypted data of the original iris data.

In order to solve the above problems, the present invention also provides an iris data recognition method, including:

Get database encrypted data;

Obtain the encrypted data of the iris data to be authenticated based on the iris data encryption method, where the iris data encryption method is the steps in the iris data encryption method described above;

According to the Hamming distance calculation formula, calculate the Hamming distance of the encrypted data to be authenticated and the encrypted data of the database respectively to obtain the distance to be authenticated;

Set distance threshold;

When the distance to be authenticated is not greater than the distance threshold, it is determined that the iris data to be authenticated is successfully authenticated.

Furthermore, the calculation formula of Hamming distance is:

Among them, Dis(t ^′ , d) is the Hamming distance, t _i ^′ is the i-th block in the encrypted data t ^′ to be authenticated, d _i is the i-th block in the database encrypted data d, and the value range of i is [ 1, 10×m], m is the total amount of data blocks.

In order to solve the above problems, the present invention also provides an electronic device, including a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, the iris data encryption method as described above is implemented, or, as above The iris data recognition method.

The beneficial effects of adopting the above embodiments are: the present invention provides an iris data encryption and identification method and electronic equipment. The encryption method realizes preliminary encryption processing of the original iris data by replacing and rearranging the original iris data, and obtains rearrangement. iris data to improve the complexity of the iris data; further, by dividing the rearranged iris data into blocks, the combined characteristics of each data block of the rearranged iris data can be obtained, and by inverting and merging each data block, the The combined features of each data block are represented as data to reduce the magnitude of the iris data; finally, the iris data is grouped by inverting and merging, and each group is sorted separately, and the sorting sequence is determined to be the encrypted data of the original iris data , Standardizing the characteristics of iris data can effectively hide the characteristics of iris data to improve the standardization of iris data and reduce data characteristics, thereby avoiding the decryption of iris data.

Description of the drawings

Figure 1 is a schematic flow chart of an embodiment of an iris data encryption method provided by the present invention;

Figure 2 is a schematic flow chart of obtaining rearranged iris data according to an embodiment of the present invention;

Figure 3 is a schematic flowchart of an embodiment of obtaining inverted and merged iris data provided by the present invention;

Figure 4 is a schematic flow chart of another embodiment of obtaining inverted and merged iris data provided by the present invention;

Figure 5 is a schematic flow chart of an embodiment of obtaining encrypted data of original iris data provided by the present invention;

Figure 6 is a schematic flow chart of an embodiment of encrypting original iris data provided by the present invention;

Figure 7 is a schematic flow chart of an embodiment of iris data recognition provided by the present invention;

FIG. 8 is a structural block diagram of an embodiment of the electronic device provided by the present invention.

Detailed ways

The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

With the rapid development of technologies such as the Internet, mobile communications and the Internet of Things, people use various devices and applications to carry out daily activities, and the large amounts of data generated by these activities may contain users' personal privacy information. With the continuous development and maturity of biometric technology, various modes of biometric technology, such as iris recognition, face recognition, fingerprint recognition, etc., have been applied in financial and people's livelihood scenarios. However, when data flows are complex, data leaks may occur and the risk of personal information being used maliciously increases. As one of the most commonly used biometric features, industry and academia have conducted extensive research on how to effectively perform iris recognition and protect the privacy of user information.

In recent years, many iris data protection methods have been proposed, which are mainly divided into two categories: revocable iris biometric technology and iris biometric encryption system. However, in the field of revocable iris recognition technology, existing technical methods include solutions based on Bloom filters, solutions based on local sensitive hashing, and solutions based on feature adaptive random projection. Since the above methods are irreversible and reversible, There is no good balance between revocability and unlinkability, and it is impossible to completely prevent the user's iris data from being decrypted, resulting in the inability to effectively guarantee the security of the user's iris data.

Therefore, in the process of protecting the security of iris data in the prior art, there is a problem that the iris data cannot be avoided from being decrypted.

In order to solve the above problems, the present invention provides an iris data encryption and identification method and electronic device, which will be described in detail below.

Figure 1 is a schematic flow chart of an embodiment of an iris data encryption method provided by the present invention. As shown in Figure 1, the iris data encryption method includes:

Step S101: Obtain original iris data;

Step S102: Perform replacement and rearrangement on the original iris data to obtain rearranged iris data;

Step S103: Divide the rearranged iris data into blocks to obtain multiple data blocks, and perform inversion and merge on the multiple data blocks respectively to obtain inversion and merged iris data;

Step S104: Group the reversed and merged iris data to obtain multiple data groups, and sort the multiple data groups respectively to obtain a sorting sequence of the reversed and merged iris data, and determine that the sorting sequence is the encrypted data of the original iris data.

In this embodiment, first, the original iris data is obtained, and the original iris data is replaced and rearranged to obtain the rearranged iris data; then, the rearranged iris data is divided into blocks, and each data block is inverted and merged to obtain Invert and merge the iris data; finally, group the inverse and merged iris data, and sort each group respectively to obtain the sorting sequence of the inverse and merged iris data, and determine that the sorting sequence is the encrypted data of the original iris data.

In this embodiment, by performing replacement and rearrangement of the original iris data, preliminary encryption processing of the original iris data is achieved, and the rearranged iris data is obtained to improve the complexity of the iris data; further, by analyzing the rearranged iris data, block, the combined characteristics of each data block of rearranged iris data can be obtained, and by inverting and merging each data block, the combined characteristics of each data block can be represented as data, and the magnitude of the iris data can be reduced; finally, By grouping the inverted and merged iris data, sorting each group separately, and determining that the sorting sequence is the encrypted data of the original iris data, and standardizing the characteristics of the iris data, the characteristics of the iris data can be effectively hidden to improve the quality of the iris data. The degree of standardization reduces data characteristics to prevent iris data from being decrypted.

As a preferred embodiment, in step S101, the original iris data is a binary string of length n.

In a specific embodiment, the iris data in the data set CASIA-IrisV3-Interval is converted into a binary string with a length of 10240 bits after preprocessing operations such as segmentation and feature extraction, thereby obtaining original iris data with a length of 10240 bits. , that is, the value of n is 10240.

As a preferred embodiment, in step S102, in order to obtain rearranged iris data, as shown in Figure 2, Figure 2 is a schematic flow chart of obtaining rearranged iris data according to an embodiment of the present invention, including:

Step S121: Obtain a random replacement string;

Step S122: Based on the random replacement string, perform replacement and rearrangement of the original iris data to obtain rearranged iris data;

Among them, the length of the random replacement string is the same as the length of the original iris data, and the numbers in the random replacement string do not repeat.

In this embodiment, a random permutation string is obtained to obtain a random data string sequence with the same length as the original iris data, and then the random permutation string is used as the sequence number of the original iris data, and the original iris data is permuted and rearranged to obtain Rearrange iris data.

It should be noted that the random permutation string includes multiple natural numbers with the same length value as the original iris data, so that for any single original iris data, there is a unique random permutation string value corresponding to it.

In a specific embodiment, in step S121, a random permutation string K of the same length n is generated through the rand() function, which can be expressed as K=K ₁ ...K _n .

It should be noted that each value in K is different, and K includes each value from 1 to n.

In a specific embodiment, in step S122, in order to perform replacement and rearrangement of the original iris data, when K ₁ =8, it means that the data at the first position in the original iris data x must be the same as the data at the 8th position. The data on is exchanged; when K ₂ =18, it means that the data at the second position in the original iris data x needs to be exchanged with the data at the 18th position, and so on, which will not be described in detail here.

After this step of random replacement, we get the disrupted and rearranged iris template. That is, rearrange the iris data.

In other embodiments, the original iris data can also be rearranged according to other random replacement methods to achieve preliminary encryption of the original iris data.

In addition, it should be noted that for the original iris data and the iris data to be authenticated in the same system, the random replacement string K is completely consistent.

As a preferred embodiment, in step S103, in order to divide the rearranged iris data into blocks, perform inverse merging of each data block to obtain the inverse combined iris data, as shown in Figure 3, which is provided by the present invention. A schematic flowchart of an embodiment of obtaining inverted and merged iris data, including:

Step S131: Set the blocking bit width, and divide the rearranged iris data into multiple data blocks according to the blocking bit width;

Step S132: Convert binary data in multiple data blocks into decimal data to obtain multiple decimal iris data;

Step S133: According to the block bit width and the decimal standard value calculation formula, obtain the decimal standard value;

Step S134: Invert and merge multiple decimal iris data according to the decimal standard value to obtain the inverted and merged iris data.

In this embodiment, first, set the block bit width, and divide the rearranged iris data into multiple data blocks according to the block bit width; next, convert the binary data in the multiple data blocks into decimal data, and obtain Multiple decimal iris data; then, according to the block bit width, based on the decimal standard value calculation formula, the decimal standard value is obtained; finally, based on the decimal standard value, multiple decimal iris data are inverted and merged to obtain the inverted and merged iris data .

In this embodiment, by setting the block bit width and dividing the rearranged iris data into multiple data blocks, the combined characteristics of each data block of the rearranged iris data can be obtained to hide specific local features; by dividing multiple data blocks into The binary data in the data block is converted into decimal data, which can more accurately represent the characteristics of each part to facilitate subsequent data processing; through the decimal standard value calculation formula, the decimal standard value is obtained, and the inverted and merged comparison standard data is obtained; By inverting and merging multiple decimal iris data, the inverted and merged iris data is obtained, thereby achieving unified and standardized processing of decimal iris data to improve the efficiency of subsequent data processing.

As a preferred embodiment, in step S131, the iris template Divided into m blocks, expressed as Each block contains b bits.

In a specific embodiment, the specific value of m can be adjusted according to actual needs, and can be any positive integer greater than 1.

Specifically, m preferably takes a value of 4.

As a preferred embodiment, in step S132, the binary values in m blocks are converted into corresponding decimal values w, and expressed as w=w ₁ ...w _m .

Among them, after the binary value is converted into a decimal value, each block has only unique decimal value data to represent its characteristics.

In this embodiment, by converting the binary value into a decimal value, the data level of the iris data is substantially reduced, the amount of subsequent processing is reduced, and the data characteristics are hidden.

As a preferred embodiment, in step S133, the decimal standard value calculation formula is:

S＝2 ^b-1 -1

Among them, S is the decimal standard value, and b is the block bit width.

As a preferred embodiment, in step S134, in order to perform inversion and merge on multiple decimal iris data according to the decimal standard value, the inversion and merged iris data are obtained, as shown in Figure 4. Figure 4 is the obtained inversion and merged iris data provided by the present invention. A schematic flowchart of another embodiment of demerging iris data, including:

Step S1341: Determine the sizes of multiple decimal iris data and decimal standard values in sequence;

Step S1342: When the decimal iris data is greater than the decimal standard value, based on the inversion formula, determine the inverted combined iris data corresponding to the decimal iris data;

Step S1343: When the decimal iris data is not greater than the decimal standard value, determine that the decimal iris data is its corresponding inverted merged iris data.

In this embodiment, first, the sizes of multiple decimal iris data and decimal standard values are sequentially determined to determine the data value size relationship between the decimal iris data and the decimal standard value; then, when the decimal iris data is greater than the decimal standard value , based on the inversion formula, determine the inverted combined iris data corresponding to the decimal iris data; when the decimal iris data is not greater than the decimal standard value, determine that the decimal iris data is the corresponding inverted combined iris data.

In this embodiment, by setting the decimal standard value as the standard for data processing of decimal iris data, only when the decimal iris data is greater than the decimal standard value, the decimal iris data is revised by combining the inversion formula, thereby realizing the decimal iris data The further unification reduces the difference of iris data and increases the difficulty of cracking and inverting the merged iris data.

As a preferred embodiment, in step S1342, the inverse formula is:

r _i =2 ^b -1-w _i

Among them, r _i is the inverted merged iris data, and w _i is the decimal iris data.

In a specific embodiment, the decimal value w _i (i=1...m) corresponding to each block is compared with S. If w _i is larger than S, an inversion operation is performed on it, and the inverted value is The value of _w is represented by r; if w _i is less than or equal to S, the value of w _i remains unchanged, that is, r _i = _wi .

In this embodiment, by performing an inversion and merging operation on the iris data, the value of the iris data is reduced, thereby reducing the difficulty of subsequent data processing and further hiding the characteristics of the iris data.

As a preferred embodiment, in step S104, in order to group the reversed merged iris data and sort each group respectively, obtain a sorting sequence of the reversed merged iris data, and determine that the sorting sequence is the encrypted data of the original iris data , as shown in Figure 5, Figure 5 is a schematic flow chart of an embodiment of obtaining encrypted data of original iris data provided by the present invention, including:

Step S141: Set the grouping width, and divide the inverted merged iris data into multiple data groups according to the grouping width;

Step S142: Sort the inverted and merged iris data in multiple data groups according to the size of the data values, and obtain multiple sorting sequences corresponding to the multiple data groups;

Step S143: Determine the sorting sequence to be the encrypted data of the original iris data.

In this embodiment, first, set the grouping width, and divide the reversed merged iris data into multiple data groups according to the grouping width; then, sort the reversed merged iris data in the multiple data groups according to the size of the data value. , multiple sorting sequences corresponding to multiple data groups are obtained; finally, the sorting sequence is determined to be the encrypted data of the original iris data.

In this embodiment, by setting the grouping width, the inverted and merged iris data is once again divided into groups to obtain multiple data groups, thereby dividing the characteristics of the iris data into blocks and hiding specific local features; by using data The size of the value is used as a comparison benchmark. The reversed and merged iris data in multiple data groups are sorted respectively to obtain multiple sorting sequences corresponding to multiple data groups, and finally the sorting sequence is determined to be the encrypted data of the original iris data, realizing the The indiscriminate processing of multiple data groups effectively reduces the particularity of the encrypted data, further hiding the specific characteristics of the encrypted data and reducing the risk of being decrypted.

As a preferred embodiment, in step S141, the inverted merged iris data r is divided into g groups, and expressed as R=R ₁ ...R _g .

Among them, the group width is set to d, that is, each group contains d blocks, and satisfies:

m=g×d.

In a specific embodiment, d takes a value of 3.

As a preferred embodiment, in step S142, sorting is performed in each group according to the decimal value size corresponding to each block, and the sorting value corresponding to the inverted merged iris data in each block is recorded.

It should be noted that when there are multiple blocks with the same corresponding decimal value in a group, the sorting values of these blocks will be determined based on their arrangement order value within the group. For example, when the decimal value in the first group R ₁ is {3, 1, 3}, the final corresponding sorting value should be {1, 0, 2}.

In order to better represent the above data processing process, as shown in Figure 6, Figure 6 is a schematic flow chart of an embodiment of encrypting original iris data provided by the present invention.

Through the above method, the encryption processing of the original iris data is realized. However, the length of the protected encrypted data generated above will be reduced compared with the original iris data, resulting in the loss of part of the iris feature information. In order to expand the length of the encrypted data template and thereby improve the accuracy in the recognition process, ten different The random permutation strings K ¹ ...K ¹⁰ perform the above encryption operation on the same piece of original iris data, thereby obtaining 10 corresponding encrypted data templates t ¹ ...t ¹⁰ .

Further, the 10 encrypted data templates are spliced into a long iris string t, which is expressed as t=t ¹ ||...||t ¹⁰ , thereby obtaining the finally generated protected iris template t, whose length is 10×m.

In other embodiments, the number of random permutation strings K can also be adjusted as needed.

Through the above method, when the attacker obtains the final protected iris template t, he actually obtains the ranking value of each block within the group. Due to the intra-group local sorting process in the previously generated template, the process of recovering the corresponding decimal values from the sorted values of individual blocks in the protected iris template is a many-to-one mapping process. When the sorting value of a block is determined, there will be multiple choices for the decimal value corresponding to the block, thereby increasing the difficulty of recovery and enhancing irreversibility. When the decimal value corresponding to the block is obtained, since the original block was inverted and merged in the previous process of generating the template, the real decimal value corresponding to the decimal value of each block in the protected iris template here is actually There are two possibilities, keep the original value or perform an inversion operation. Since each iris string contains a large number of blocks, there are many possibilities. This step greatly enhances the randomness of the scheme, making it more difficult to recover the original iris template.

Based on the above iris data encryption method, iris data can be encrypted to improve the reliability of iris data and avoid being decrypted by others; further, this application also provides an iris data identification method to satisfy internal personnel's use of iris data The need for encryption authentication is as shown in Figure 7. Figure 7 is a schematic flow chart of an embodiment of iris data recognition provided by the present invention, including:

Step S201: Obtain database encrypted data;

Step S202: Obtain the encrypted data of the iris data to be authenticated based on the iris data encryption method;

Step S203: According to the Hamming distance calculation formula, calculate the Hamming distance of the encrypted data to be authenticated and the encrypted data of the database respectively to obtain the distance to be authenticated;

Step S204: Set distance threshold;

Step S205: When the distance to be authenticated is not greater than the distance threshold, determine that the iris data to be authenticated is successfully authenticated;

Wherein, the iris data encryption method is a step in the iris data encryption method described in any of the above technical solutions.

In this embodiment, first, based on the iris data encryption method for obtaining database encrypted data, the iris data to be authenticated is encrypted to obtain the encrypted data to be authenticated; then, according to the Hamming distance calculation formula, the encrypted data to be authenticated and the database encryption are calculated respectively. The Hamming distance of the data is used to obtain the distance to be authenticated; finally, by setting the distance threshold, only when the distance to be authenticated is not greater than the distance threshold, the authentication of the iris data to be authenticated is determined to be successful.

In this embodiment, due to the complexity and uncontrollable structure of decryption, on the one hand, the iris data encryption method is used as the preliminary data processing method for the iris data to be authenticated, which effectively avoids the process of reverse decryption of the iris data to be authenticated; on the other hand, the iris data encryption method is used as the preliminary data processing method for the iris data to be authenticated. On the one hand, the distance threshold is used as a benchmark to compare the quantitative relationship between the distance to be authenticated and the distance threshold, thereby determining whether the iris data to be authenticated is iris data in the database, that is, determining whether the person corresponding to the iris data to be authenticated is already registered. And the iris data of the person exists in the database.

As a preferred embodiment, in step S202, the random substitution string K used in the process of obtaining the encrypted data to be authenticated is the same as the random substitution string K used to generate the database encrypted data in step S201.

As a preferred embodiment, in step S203, the Hamming distance calculation formula is:

Among them, Dis(t ^′ , d) is the Hamming distance, t _i ^′ is the i-th block in the encrypted data t ^′ to be authenticated, d _i is the i-th block in the database encrypted data d, and the value range of i is [ 1, 10×m], m is the total amount of data blocks.

In a specific embodiment, the user submits his or her own iris data x ^′ to the server, and the protected iris template ^{t ′} is generated on the server through a designed iris template generation scheme based on inverse merging and local sorting. The Hamming distance between t ^′ and the iris template in the iris template database is calculated on the server and compared with the threshold C. When it is less than or equal to the threshold C, it indicates that the recognition is successful. If the distance between t ^′ and all iris templates in the iris template database is greater than the threshold C, it means that the recognition fails. Experimental results prove that this method can effectively protect the user's iris feature data while achieving good recognition results.

Through the above method, the original iris data is replaced and rearranged to achieve preliminary encryption processing of the original iris data, and the rearranged iris data is obtained to improve the complexity of the iris data; further, by dividing the rearranged iris data into blocks , the combined features of each data block of the rearranged iris data can be obtained, and by inverting and merging each data block, the combined features of each data block can be represented as data, and the magnitude of the iris data can be reduced; finally, by Invert and merge the iris data into groups, sort each group separately, and determine the sorting sequence as the encrypted data of the original iris data. Standardize the characteristics of the iris data, which can effectively hide the characteristics of the iris data to improve the standardization of the iris data. , reduce data characteristics to avoid iris data from being decrypted.

In a specific embodiment, combined with the iris data recognition process, the processing of iris data is described in detail. First, the data set is preprocessed. The data set used is the commonly used iris data CASIA-IrisV3-Interval. The USIT system is used to The iris images in the data set are segmented; then, the iris features are extracted from the iris images, and a string of iris templates with a length of 20×512=10240 is obtained. For the dataset images used in the experiments, there were a total of 2639 iris images from 249 individuals, and only images from the left eye were used.

In order to verify the performance of the proposed privacy-preserving iris recognition method, the false acceptance rate (FalseAcceptance Rate, FAR), false rejection rate (False Rejection Rate, FRR), correct acceptance rate (GenuineAcceptance Rate, GAR) and equal error rate (Equal Error Rate, EER) four indicators to quantify the recognition effect of this method.

When the matching threshold C is determined, FAR indicates the number of times that iris data from different categories are recognized as iris data from the same category as a percentage of the total number of tests; FRR indicates that iris data from the same category is recognized as iris data from different categories. The number of times accounts for the percentage of the total number of tests; GAR represents the number of times the iris data is recognized as the correct category as a percentage of the total number of tests; EER represents the FAR value or FRR value, EER value when FAR=FRR by transforming the threshold C The smaller the value, the better the recognition performance of the system.

Among them, the calculation formulas of FAR, FRR and GAR are as follows:

Through the above method, it was found that the many-to-one mapping relationship between the inversion merge operation and the local sorting process is used, which greatly increases the attacker's options in the recovery process. The original iris template is recovered from the generated protected template. It is very difficult; use multiple random substitution strings K to operate on the same original iris template to generate multiple protected templates. By amplifying the length of the iris template, the loss of iris feature information during the template generation process is reduced; it can be better identified Extract the iris data from the database to achieve data matching.

The present invention also provides an electronic device, as shown in Figure 8. Figure 8 is a structural block diagram of an embodiment of the electronic device provided by the present invention. The electronic device 800 may be a mobile terminal, a desktop computer, a notebook, a PDA, a server and other computing devices. The electronic device 800 includes a processor 801 and a memory 802, where an iris data encryption program 803 is stored on the memory 802.

Memory 802 may, in some embodiments, be an internal storage unit of the computer device, such as a hard drive or memory of the computer device. In other embodiments, the memory 802 may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, or a flash memory equipped on the computer device. Flash Card, etc. Further, the memory 802 may also include both an internal storage unit of the computer device and an external storage device. The memory 802 is used to store application software and various types of data installed on the computer device, such as program codes installed on the computer device. The memory 802 may also be used to temporarily store data that has been output or is to be output. In one embodiment, the iris data encryption program 803 can be executed by the processor 801, thereby implementing the iris data encryption methods of various embodiments of the present invention.

In some embodiments, the processor 801 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run program codes stored in the memory 802 or process data, such as performing iris data encryption. Programs etc.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage. In the media, when executed, the computer program may include the processes of the above method embodiments. Any reference to memory, storage, databases, or other media used in the various embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Synchlink DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

The above are only preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person familiar with the technical field can easily think of changes or modifications within the technical scope disclosed in the present invention. All substitutions are within the scope of the present invention.

Claims (10)

1. An iris data privacy protection method, comprising:

acquiring original iris data;

performing replacement rearrangement on the original iris data to obtain rearranged iris data;

partitioning the rearranged iris data to obtain a plurality of data blocks, and respectively performing inverse merging on the plurality of data blocks to obtain inverse merging iris data;

grouping the inverse merging iris data to obtain a plurality of data groups, respectively ordering the plurality of data groups to obtain an ordering sequence of the inverse merging iris data, and determining the ordering sequence as the encrypted data of the original iris data.

2. The method for protecting the privacy of iris data according to claim 1, wherein the performing permutation rearrangement on the original iris data to obtain rearranged iris data comprises:

acquiring a random substitution string, wherein the length of the random substitution string is the same as the length of the original iris data, and the numbers in the random substitution string are not repeated;

and based on the random substitution string, carrying out substitution rearrangement on the original iris data to obtain rearranged iris data.

3. The method of claim 1, wherein the partitioning the rearranged iris data to obtain a plurality of data blocks, and respectively performing inverse merging on the plurality of data blocks to obtain inverse merged iris data, includes:

setting a block bit width, and equally dividing the rearranged iris data into a plurality of data blocks according to the block bit width;

converting binary data in the plurality of data blocks into decimal data to obtain a plurality of decimal iris data;

according to the block bit width, a decimal standard value is obtained based on a decimal standard value calculation formula;

and according to the decimal standard value, performing inverse merging on the decimal iris data to obtain inverse merging iris data.

4. The method for protecting privacy of iris data according to claim 3, wherein the decimal standard value calculation formula is:

S＝2 ^b-1 -1

wherein S is the decimal standard value and b is the block bit width.

5. The method of claim 4, wherein the performing inverse merging on the plurality of decimal iris data according to the decimal standard value to obtain inverse merged iris data comprises:

sequentially judging the sizes of the decimal iris data and the decimal standard value respectively;

when the decimal iris data is larger than the decimal standard value, determining the inverse combined iris data corresponding to the decimal iris data based on an inverse formula;

and when the decimal iris data is not larger than the decimal standard value, determining that the decimal iris data is the corresponding inverse combined iris data.

6. The method of claim 5, wherein the inverse formula is:

r _i ＝2 ^b -1-w _i

wherein r is _i Combining iris data for the inversion, w _i And (3) the decimal iris data.

7. The method of claim 1, wherein the grouping the inverse merging iris data to obtain a plurality of data sets, and sorting the plurality of data sets respectively to obtain a sorted sequence of the inverse merging iris data, and determining the sorted sequence as the encrypted data of the original iris data, comprises:

setting a grouping width, and dividing the inverse merging iris data into a plurality of data groups according to the grouping width;

sorting the inverse merging iris data in the plurality of data sets according to the data value, so as to obtain a plurality of sorting sequences corresponding to the plurality of data sets;

and determining the ordered sequence as the encrypted data of the original iris data.

8. An iris data recognition method, comprising:

acquiring database encryption data;

obtaining encrypted data to be authenticated of iris data to be authenticated based on an iris data encryption method, wherein the iris data encryption method is the steps in the iris data encryption method according to any one of the claims 1 to 7;

respectively calculating the Hamming distance between the encrypted data to be authenticated and the encrypted data of the database according to a Hamming distance calculation formula to obtain the distance to be authenticated;

setting a distance threshold;

and when the distance to be authenticated is not greater than the distance threshold, judging that the iris data to be authenticated is successfully authenticated.

9. The iris data recognition method of claim 8, wherein the hamming distance calculation formula is:

wherein Dis (t) ^′ D) is the Haiming distance, t _i ^′ Encrypting data t for the to-be-authenticated ^′ The ith block, d _i The value range of i is [1, 10×m ] for the ith block in the database encryption data d]M is the total amount of data blocks.

10. An electronic device comprising a processor and a memory, the memory having stored thereon a computer program which, when executed by the processor, implements the iris data privacy protection method of any of claims 1-7 or the iris data recognition method of any of claims 8-9.