Iris data privacy protection, identification method and electronic device

Abstract

The application provides an iris data privacy protection method, an identification method and an electronic device. The privacy protection method realizes preliminary encryption processing of original iris data by performing permutation and rearrangement on the original iris data, obtains rearranged iris data, and improves the complexity of the iris data. Further, by performing block division on the rearranged iris data, the combination features of each data block of the rearranged iris data can be obtained, and by performing inversion and merging on each data block, the combination features of each data block can be represented by data, and the magnitude of the iris data can be reduced. Finally, by performing grouping on the inversion and merging iris data, and sorting each group respectively, and determining the sorting sequence as the encrypted data of the original iris data, the features of the standardized iris data can be effectively hidden, the standardization degree of the iris data is improved, the data characteristics are reduced, and thus the iris data is prevented from being decrypted.

Description

Technical Field

[0001] This invention relates to the field of privacy protection and security technology, specifically to an iris data privacy protection and identification method and electronic device. Background Technology

[0002] With the rapid development of technologies such as the Internet, mobile communications, and the Internet of Things (IoT), people use various devices and applications for daily activities, generating vast amounts of data that may contain users' personal privacy information. As biometric technologies continue to develop and mature, various biometric technologies, such as iris recognition, facial recognition, and fingerprint recognition, have been applied in financial and public service scenarios. However, in situations involving complex data flows, the risk of data breaches and malicious use of personal information may increase. As one of the most commonly used biometric features, iris recognition has been the subject of extensive research in industry and academia on how to effectively perform iris recognition while protecting user privacy.

[0003] In recent years, many iris data protection methods have been proposed, mainly falling into two categories: revocable iris biometrics and iris biometric encryption systems. However, in the field of revocable iris recognition technology, existing methods include Bloom filter-based schemes, Locality Sensitive Hashing (LSH)-based schemes, and Feature Adaptive Random Projection (LARP) schemes. Because these methods do not achieve a good balance between irreversibility, revocability, and non-linkability, they cannot completely prevent the decryption of users' iris data, thus failing to effectively guarantee the security of users' iris data.

[0004] Therefore, in the process of protecting iris data security in the existing technology, there is a problem that the iris data cannot be decrypted. Summary of the Invention

[0005] In view of this, it is necessary to provide an iris data privacy protection and identification method and electronic device to solve the problem that the iris data cannot be decrypted in the process of protecting the security of iris data in the prior art.

[0006] To address the above problems, this invention provides a method for protecting iris data privacy, comprising:

[0007] Obtain raw iris data;

[0008] The original iris data is permuted and rearranged to obtain rearranged iris data;

[0009] The rearranged iris data is divided into blocks to obtain multiple data blocks, and the multiple data blocks are inverted and merged to obtain inverted and merged iris data.

[0010] The inverted and merged iris data is grouped into multiple data groups, and each data group is sorted to obtain a sorted sequence of the inverted and merged iris data. The sorted sequence is then determined to be the encrypted data of the original iris data.

[0011] Furthermore, the original iris data is permuted and rearranged to obtain rearranged iris data, including:

[0012] Obtain a random permutation string, wherein 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 are not repeated;

[0013] Based on the random permutation string, the original iris data is permuted and rearranged to obtain rearranged iris data.

[0014] Furthermore, the rearranged iris data is divided into blocks to obtain multiple data blocks, and each data block is inverted and merged to obtain inverted and merged iris data, including:

[0015] Set the block bit width and divide the rearranged iris data into multiple data blocks according to the block bit width;

[0016] The binary data in multiple data blocks is converted into decimal data to obtain multiple decimal iris data;

[0017] Based on the block bit width, the decimal standard value is obtained using the decimal standard value calculation formula.

[0018] Based on the decimal standard value, multiple decimal iris data are inverted and merged to obtain inverted and merged iris data.

[0019] Furthermore, the formula for calculating the decimal standard value is as follows:

[0020] S = 2 b-1 -1

[0021] Where S is the decimal standard value and b is the block bit width.

[0022] Furthermore, based on the decimal standard value, multiple decimal iris data are inverted and merged to obtain inverted and merged iris data, including:

[0023] The values ​​of multiple decimal iris data and decimal standard values ​​are determined sequentially.

[0024] When the decimal iris data is greater than the decimal standard value, the corresponding inverted and merged iris data is determined based on the inversion formula.

[0025] When the decimal iris data is not greater than the decimal standard value, the decimal iris data is determined to be the corresponding inverted and merged iris data.

[0026] Furthermore, the inverse formula is:

[0027] r i =2 b -1-w i

[0028] Where, r i To invert and merge iris data, w i The data is in decimal iris format.

[0029] Furthermore, the inverted and merged iris data is grouped into multiple data groups, and each data group is sorted to obtain a sorted sequence of the inverted and merged iris data. This sorted sequence is then identified as the encrypted data of the original iris data, including:

[0030] Set the group width and divide the inverted and merged iris data into multiple data groups according to the group width;

[0031] Based on the size of the data values, the inverted and merged iris data in multiple data groups are sorted to obtain multiple sorting sequences corresponding to multiple data groups;

[0032] The sorted sequence is determined to be encrypted data of the original iris data.

[0033] To address the above problems, the present invention also provides an iris data recognition method, comprising:

[0034] Retrieve encrypted data from the database;

[0035] The iris data encryption method is used to obtain the encrypted data to be authenticated based on the iris data encryption method described above.

[0036] Based on the Hamming distance calculation formula, the Hamming distance between the encrypted data to be authenticated and the encrypted data in the database is calculated respectively to obtain the authentication distance;

[0037] Set a distance threshold;

[0038] When the distance to be authenticated is not greater than the distance threshold, the iris data to be authenticated is deemed to be successfully authenticated.

[0039] Furthermore, the formula for calculating the Hamming distance is:

[0040]

[0041] Where Dis(t) ′ ,d) is the Hamming distance, t i ′ Encrypt the data to be authenticated t ′ The i-th block in d iEncrypt the i-th block of data d in the database, where i ranges from [1, 10×m] and m is the total number of data blocks.

[0042] To address the aforementioned problems, the present invention also provides an electronic device, including a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it implements the iris data encryption method or the iris data recognition method described above.

[0043] The beneficial effects of the above embodiments are as follows: The present invention provides an iris data encryption and recognition method and electronic device. The encryption method performs preliminary encryption processing on the original iris data by permuting and rearranging it to obtain rearranged iris data, thereby increasing the complexity of the iris data. Furthermore, by dividing the rearranged iris data into blocks, the combination features of each data block of the rearranged iris data can be obtained. By inverting and merging each data block, the combination features of each data block can be represented as data, thereby reducing the magnitude of the iris data. Finally, by grouping the inverted and merged iris data and sorting each group, the sorted sequence is determined as the encrypted data of the original iris data. The standardized processing of the iris data features can effectively hide the features of the iris data, thereby improving the standardization degree of the iris data, reducing data characteristics, and thus preventing the iris data from being decrypted. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating an embodiment of the iris data encryption method provided by the present invention;

[0045] Figure 2 This is a schematic flowchart of an embodiment of obtaining rearranged iris data provided by the present invention;

[0046] Figure 3 This is a schematic flowchart of an embodiment of the present invention for obtaining inverted and merged iris data;

[0047] Figure 4 This is a schematic flowchart illustrating another embodiment of the present invention for obtaining inverted and merged iris data;

[0048] Figure 5 A schematic flowchart illustrating an embodiment of obtaining encrypted data from raw iris data provided by the present invention;

[0049] Figure 6 This is a flowchart illustrating an embodiment of encrypting raw iris data provided by the present invention.

[0050] Figure 7 This is a schematic flowchart of an embodiment of iris data recognition provided by the present invention;

[0051] Figure 8A structural block diagram of an embodiment of the electronic device provided by the present invention. Detailed Implementation

[0052] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form 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.

[0053] With the rapid development of technologies such as the Internet, mobile communications, and the Internet of Things (IoT), people use various devices and applications for daily activities, generating vast amounts of data that may contain users' personal privacy information. As biometric technologies continue to develop and mature, various biometric technologies, such as iris recognition, facial recognition, and fingerprint recognition, have been applied in financial and public service scenarios. However, in situations involving complex data flows, the risk of data breaches and malicious use of personal information may increase. As one of the most commonly used biometric features, iris recognition has been the subject of extensive research in industry and academia on how to effectively perform iris recognition while protecting user privacy.

[0054] In recent years, many iris data protection methods have been proposed, mainly falling into two categories: revocable iris biometrics and iris biometric encryption systems. However, in the field of revocable iris recognition technology, existing methods include Bloom filter-based schemes, Locality Sensitive Hashing (LSH)-based schemes, and Feature Adaptive Random Projection (LARP) schemes. Because these methods do not achieve a good balance between irreversibility, revocability, and non-linkability, they cannot completely prevent the decryption of users' iris data, thus failing to effectively guarantee the security of users' iris data.

[0055] Therefore, in the process of protecting iris data security in the existing technology, there is a problem that the iris data cannot be decrypted.

[0056] To address the aforementioned problems, this invention provides an iris data encryption and recognition method and an electronic device, which will be described in detail below.

[0057] Figure 1 This is a flowchart illustrating an embodiment of the iris data encryption method provided by the present invention, as shown below. Figure 1 As shown, iris data encryption methods include:

[0058] Step S101: Obtain raw iris data;

[0059] Step S102: The original iris data is permuted and rearranged to obtain rearranged iris data;

[0060] Step S103: Divide the rearranged iris data into blocks to obtain multiple data blocks, and invert and merge the multiple data blocks to obtain inverted and merged iris data.

[0061] Step S104: Group the inverted and merged iris data to obtain multiple data groups, sort the multiple data groups respectively to obtain the sorted sequence of the inverted and merged iris data, and determine the sorted sequence as the encrypted data of the original iris data.

[0062] In this embodiment, firstly, the original iris data is acquired and rearranged to obtain rearranged iris data; then, the rearranged iris data is divided into blocks, and each data block is inverted and merged to obtain inverted and merged iris data; finally, the inverted and merged iris data is grouped, and each group is sorted to obtain a sorted sequence of inverted and merged iris data, and the sorted sequence is determined to be the encrypted data of the original iris data.

[0063] In this embodiment, the original iris data is permuted and rearranged to achieve preliminary encryption processing, resulting in rearranged iris data, thereby increasing the complexity of the iris data. Furthermore, by dividing the rearranged iris data into blocks, the combined features of each data block can be obtained. By inverting and merging each data block, the combined features of each data block can be represented, reducing the magnitude of the iris data. Finally, by grouping the inverted and merged iris data and sorting each group, the sorted sequence is determined as the encrypted data of the original iris data. Standardizing the iris data features effectively hides these features, improving the standardization of the iris data, reducing data characteristics, and thus preventing the iris data from being decrypted.

[0064] In a preferred embodiment, in step S101, the original iris data is a binary string of length n.

[0065] In one specific embodiment, the iris data in the dataset CASIA-IrisV3-Interval is converted into a 10240-bit binary string after preprocessing operations such as segmentation and feature extraction, thus obtaining the original iris data of length 10240, that is, n takes the value of 10240.

[0066] In a preferred embodiment, in step S102, in order to obtain rearranged iris data, such as... Figure 2 As shown, Figure 2 A schematic flowchart of an embodiment of obtaining rearranged iris data provided by the present invention includes:

[0067] Step S121: Obtain a random permutation string;

[0068] Step S122: Based on the random permutation string, the original iris data is permuted and rearranged to obtain rearranged iris data;

[0069] 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 are not repeated.

[0070] 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. Then, the random permutation string is used as the sequence number of the original iris data to permutate and rearrange the original iris data to obtain rearranged iris data.

[0071] It should be noted that the random permutation string includes multiple natural numbers with the same length as the original iris data, thus ensuring that for any single piece of original iris data, there is a unique random permutation string value corresponding to it.

[0072] In one specific embodiment, in step S121, a random permutation string K of length n is generated using the rand() function, which can be represented as K = K1...K n .

[0073] It should be noted that each value in K is different, and K includes every value from 1 to n.

[0074] In one specific embodiment, in step S122, in order to perform permutation and rearrangement on the original iris data, when K1 = 8, it means that the data at the first position in the original iris data x is to be exchanged with the data at the 8th position; when K2 = 18, it means that the data at the second position in the original iris data x is to be exchanged with the data at the 18th position, and so on, which will not be elaborated here.

[0075] After this random permutation step, we obtained the shuffled and rearranged iris template. This involves rearranging the iris data.

[0076] In other embodiments, the original iris data can be rearranged according to other random permutation methods to achieve preliminary encryption of the original iris data.

[0077] Additionally, it should be noted that the random permutation string K is completely identical for the original iris data and the iris data to be authenticated within the same system.

[0078] In a preferred embodiment, in step S103, in order to divide the rearranged iris data into blocks and invert and merge each data block to obtain inverted and merged iris data, as follows: Figure 3 As shown, Figure 3 A flowchart illustrating an embodiment of obtaining inverted and merged iris data provided by the present invention includes:

[0079] Step S131: Set the block bit width and divide the rearranged iris data into multiple data blocks according to the block bit width;

[0080] Step S132: Convert the binary data in multiple data blocks into decimal data to obtain multiple decimal iris data;

[0081] Step S133: Based on the block bit width and the decimal standard value calculation formula, obtain the decimal standard value;

[0082] Step S134: Based on the decimal standard value, invert and merge multiple decimal iris data to obtain inverted and merged iris data.

[0083] In this embodiment, firstly, the block bit width is set, and the rearranged iris data is divided into multiple data blocks according to the block bit width; next, the binary data in the multiple data blocks is converted into decimal data to obtain multiple decimal iris data; then, based on the block bit width and the decimal standard value calculation formula, the decimal standard value is obtained; finally, based on the decimal standard value, the multiple decimal iris data are inverted and merged to obtain inverted and merged iris data.

[0084] In this embodiment, by setting the block bit width, the rearranged iris data is divided into multiple data blocks, which can obtain the combined features of each data block of the rearranged iris data to hide specific local features. By converting the binary data in multiple data blocks into decimal data, the features of each part can be represented more concisely, which is convenient for subsequent data processing. By using the decimal standard value calculation formula, a decimal standard value is obtained, and the comparison standard data for inversion and merging is obtained. By inverting and merging multiple decimal iris data, inverted and merged iris data is obtained, realizing the unified and standardized processing of decimal iris data, thereby improving the efficiency of subsequent data processing.

[0085] In a preferred embodiment, in step S131, the iris template is... Divide into m blocks, represented as Each block contains b bits.

[0086] In one specific embodiment, the specific value of m can be adjusted according to actual needs, and can take any positive integer greater than 1.

[0087] Specifically, the preferred value for m is 4.

[0088] In a preferred embodiment, in step S132, the binary values ​​in the m blocks are converted into corresponding decimal values ​​w, and represented as w = w1...w m .

[0089] In this process, after the binary value is converted to a decimal value, each block contains only a unique decimal value to represent its characteristics.

[0090] In this embodiment, by converting binary values ​​to decimal values, the data volume of iris data is substantially reduced, the amount of subsequent processing is reduced, and the data features are also hidden.

[0091] In a preferred embodiment, the formula for calculating the decimal standard value in step S133 is as follows:

[0092] S = 2 b-1 -1

[0093] Where S is the decimal standard value and b is the block bit width.

[0094] In a preferred embodiment, in step S134, in order to invert and merge multiple decimal iris data according to a decimal standard value to obtain inverted and merged iris data, such as... Figure 4 As shown, Figure 4 A flowchart illustrating another embodiment of obtaining inverted and merged iris data provided by the present invention includes:

[0095] Step S1341: Sequentially determine the magnitude of multiple decimal iris data and decimal standard values;

[0096] Step S1342: When the decimal iris data is greater than the decimal standard value, determine the inverted and merged iris data corresponding to the decimal iris data based on the inversion formula;

[0097] 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 and merged iris data.

[0098] In this embodiment, firstly, the magnitudes of multiple decimal iris data and decimal standard values ​​are sequentially determined to establish the relationship between the data values ​​of the decimal iris data and the decimal standard values. Then, when the decimal iris data is greater than the decimal standard value, the corresponding inverted and merged iris data is determined based on the inversion formula. When the decimal iris data is not greater than the decimal standard value, the decimal iris data is determined to be its corresponding inverted and merged iris data.

[0099] In this embodiment, a decimal standard value is set as the standard for processing decimal iris data. Only when the decimal iris data is greater than the decimal standard value is the decimal iris data revised by combining the inversion formula. This achieves further unification of decimal iris data, reduces the differences in iris data, and increases the difficulty of cracking the inversion and merging of iris data.

[0100] In a preferred embodiment, the inversion formula in step S1342 is:

[0101] r i =2 b -1-w i

[0102] Where, r i To invert and merge iris data, w i The data is in decimal iris format.

[0103] In one specific embodiment, the decimal value w corresponding to each block is... i Compare (i = 1...m) with S, if w i If w is greater than S, invert it and denote the inverted value as r. i If w i Less than or equal to S, keep w i The value remains unchanged, that is, r i =w i .

[0104] In this embodiment, by performing an inversion and merging operation on the iris data, the numerical value of the iris data is reduced, thereby reducing the difficulty of subsequent data processing and further hiding the characteristics of the iris data.

[0105] In a preferred embodiment, in step S104, in order to group the inverted and merged iris data and sort each group to obtain a sorted sequence of the inverted and merged iris data, and to determine that the sorted sequence is the encrypted data of the original iris data, such as... Figure 5 As shown, Figure 5 A schematic flowchart illustrating an embodiment of obtaining encrypted data from raw iris data provided by the present invention includes:

[0106] Step S141: Set the group width and divide the inverted and merged iris data into multiple data groups according to the group width;

[0107] Step S142: Sort the inverted and merged iris data in multiple data groups according to the size of the data values ​​to obtain multiple sorting sequences corresponding to the multiple data groups;

[0108] Step S143: Determine that the sorted sequence is encrypted data of the original iris data.

[0109] In this embodiment, firstly, the group width is set, and the inverted and merged iris data is divided into multiple data groups according to the group width; then, the inverted and merged iris data in the multiple data groups are sorted according to the data value size to obtain multiple sorting sequences corresponding to the multiple data groups; finally, the sorting sequence is determined to be the encrypted data of the original iris data.

[0110] In this embodiment, by setting the grouping width, the inverted and merged iris data is further divided into blocks to obtain multiple data groups. This achieves the segmentation of the characteristics of the iris data and hides specific local features. By using the data value size as a comparison benchmark, the inverted and merged iris data in multiple data groups are sorted to obtain multiple sorting sequences corresponding to multiple data groups. Finally, the sorting sequence is determined to be the encrypted data of the original iris data. This achieves indiscriminate processing of multiple data groups, effectively reducing the special nature of the encrypted data, further hiding the specific features of the encrypted data, and reducing the risk of decryption.

[0111] In a preferred embodiment, in step S141, the inverted and merged iris data r is divided into g groups, and represented as R = R1...R g .

[0112] The group width is set to d, meaning each group contains d blocks, and satisfies the following:

[0113] m = g × d.

[0114] In one specific embodiment, d is set to 3.

[0115] In a preferred embodiment, in step S142, the data in each group is sorted according to the decimal value corresponding to each block, and the sorting value corresponding to the inverted and merged iris data in each block is recorded.

[0116] It should be noted that when a group contains multiple blocks with the same corresponding decimal value, the sort value of these blocks will be determined based on their order within the group. For example, if the decimal value in the first group R1 is {3, 1, 3}, the final sort value should be {1, 0, 2}.

[0117] To better represent the above data processing procedure, such as Figure 6 As shown, Figure 6 This is a schematic flowchart illustrating an embodiment of encrypting raw iris data provided by the present invention.

[0118] The above method achieves encryption of the original iris data. However, the length of the generated protected encrypted data is smaller than that of the original iris data, leading to the loss of some iris feature information. To increase the length of the encrypted data template and thus improve the accuracy of the recognition process, ten different random permutation strings K are used. 1 ...K 10 The above encryption operation is performed on the same original iris data to obtain 10 corresponding encrypted data templates t. 1 ...t 10 .

[0119] Furthermore, the 10 encrypted data templates are concatenated into a long iris string t, which is represented as t = t 1 ||...||t 10 Thus, the final protected iris template t is obtained, with a length of 10×m.

[0120] In other embodiments, the number of random permutation strings K can be adjusted as needed.

[0121] Using the above method, when an attacker obtains the final protected iris template t, they actually obtain the sorting value of each block within the group. Due to the local sorting process within the group during template generation, the process of recovering the corresponding decimal value from the sorting value of each block in the protected iris template is a many-to-one mapping process. When the sorting value of a block is determined, the corresponding decimal value of the block will have multiple choices, thus increasing the difficulty of recovery and enhancing irreversibility. After obtaining the decimal value corresponding to the block, because the original blocks were inverted and merged during the previous template generation process, the actual decimal value corresponding to the decimal value of each block in the protected iris template actually has two possibilities: keep the original value or invert it. 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 even more difficult to recover the original iris template.

[0122] Based on the aforementioned iris data encryption method, iris data can be encrypted to improve its reliability and prevent decryption by others. Furthermore, this application also provides an iris data recognition method to meet the needs of internal personnel for encrypted authentication using iris data, such as... Figure 7 As shown, Figure 7 A flowchart illustrating an embodiment of iris data recognition provided by the present invention includes:

[0123] Step S201: Obtain encrypted data from the database;

[0124] Step S202: Obtain the encrypted data to be authenticated from the iris data based on the iris data encryption method;

[0125] Step S203: Calculate the Hamming distance between the encrypted data to be authenticated and the encrypted data in the database according to the Hamming distance calculation formula to obtain the authentication distance;

[0126] Step S204: Set the distance threshold;

[0127] Step S205: When the distance to be authenticated is not greater than the distance threshold, the iris data to be authenticated is determined to be successfully authenticated;

[0128] The iris data encryption method is a step in the iris data encryption method described in any of the above technical solutions.

[0129] In this embodiment, firstly, based on the iris data encryption method for obtaining encrypted data from the database, the iris data to be authenticated is encrypted to obtain encrypted data to be authenticated; then, according to the Hamming distance calculation formula, the Hamming distance between the encrypted data to be authenticated and the encrypted data from the database is calculated to obtain the authentication distance; finally, by setting a distance threshold, the iris data to be authenticated is determined to be successfully authenticated only when the authentication distance is not greater than the distance threshold.

[0130] In this embodiment, due to the complexity of decryption and the uncontrollability of the structure, 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 reverse decryption process of the iris data to be authenticated; on the other 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 in the iris data in the database, that is, determining whether the person corresponding to the iris data to be authenticated is the iris data of a person who has been registered and exists in the database.

[0131] In a preferred embodiment, the random permutation string K used in step S202 to obtain the encrypted data to be authenticated is the same as the random permutation string K used in step S201 to generate the encrypted database data.

[0132] In a preferred embodiment, in step S203, the Hamming distance calculation formula is as follows:

[0133]

[0134] Where Dis(t) ′ ,d) is the Hamming distance, t i ′ Encrypt the data to be authenticated t ′ The i-th block in d i Encrypt the i-th block of data d in the database, where i ranges from [1, 10×m] and m is the total number of data blocks.

[0135] In one specific embodiment, the user submits their iris data x to the server. ′ On the server, a protected iris template t is generated using a designed iris template generation scheme based on inversion merging and local sorting. ′ Calculate t on the server. ′ The Hamming distance between the iris templates and those in the iris template database is compared to a threshold C. Successful recognition is indicated when the distance is less than or equal to the threshold C. If t ′If the distance between the iris and all iris templates in the iris template database is greater than a threshold C, then the recognition fails. Experimental results demonstrate that this method can effectively protect the user's iris feature data while achieving good recognition results.

[0136] The above method achieves preliminary encryption of the original iris data by permuting and rearranging it, resulting in rearranged iris data, thus increasing the complexity of the iris data. Furthermore, by dividing the rearranged iris data into blocks, the combined features of each data block can be obtained. By inverting and merging each data block, the combined features of each data block can be represented, reducing the magnitude of the iris data. Finally, by grouping the inverted and merged iris data and sorting each group, the sorted sequence is determined as the encrypted data of the original iris data. Standardizing the iris data features effectively hides these features, improving the standardization of the iris data, reducing data characteristics, and thus preventing the iris data from being decrypted.

[0137] In one specific embodiment, the iris data processing procedure is described in detail in conjunction with the iris data recognition process. First, the dataset is preprocessed using the commonly used iris data CASIA-IrisV3-Interval. The USIT system is used to segment the iris images in the dataset. Then, iris feature extraction is performed on the iris images to obtain a string of iris templates with a length of 20×512=10240. For the dataset images used in the experiment, there are 2639 iris images from 249 individuals, and only images from the left eye are used.

[0138] To verify the performance of the proposed privacy-preserving iris recognition method, four metrics are introduced: False Acceptance Rate (FAR), False Rejection Rate (FRR), Genuine Acceptance Rate (GAR), and Equal Error Rate (EER) to quantify the recognition effect of this method.

[0139] When the matching threshold C is determined, FAR represents the percentage of times iris data from different categories are identified as iris data from the same category out of the total number of tests; FRR represents the percentage of times iris data from the same category are identified as iris data from different categories out of the total number of tests; GAR represents the percentage of times iris data is correctly identified out of the total number of tests; EER is the FAR or FRR value when FAR = FRR after changing the threshold C. The smaller the EER value, the better the recognition performance of the system.

[0140] The calculation formulas for FAR, FRR, and GAR are as follows:

[0141]

[0142]

[0143]

[0144] The above methods reveal that by leveraging the many-to-one mapping relationship between the inversion and merging operation and the local sorting process, attackers have significantly more options during the recovery process, making it extremely difficult to recover the original iris template from the generated protected template. Using multiple random permutation strings K to operate on the same original iris template generates multiple protected templates, and by increasing the iris template length, the loss of iris feature information during template generation is reduced. This approach can effectively identify iris data in the database, enabling data matching.

[0145] The present invention also provides an electronic device, such as... Figure 8 As shown, Figure 8 This is a structural block diagram of an embodiment of the electronic device provided by the present invention. The electronic device 800 can be a computing device such as a mobile terminal, desktop computer, laptop, handheld computer, and server. The electronic device 800 includes a processor 801 and a memory 802, wherein the memory 802 stores an iris data encryption program 803.

[0146] In some embodiments, memory 802 may be an internal storage unit of a computer device, such as a hard disk or memory. In other embodiments, memory 802 may be an external storage device of a computer device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc. Further, memory 802 may include both internal and external storage units of the computer device. Memory 802 is used to store application software and various types of data installed on the computer device, such as program code for installing the computer device. Memory 802 can also be used to temporarily store data that has been output or will be output. In one embodiment, iris data encryption program 803 may be executed by processor 801 to implement the iris data encryption method of the various embodiments of the present invention.

[0147] In some embodiments, processor 801 may be a central processing unit (CPU), microprocessor or other data processing chip, used to run program code stored in memory 802 or process data, such as executing iris data encryption program.

[0148] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0149] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An iris data privacy protection method, characterized by, include: Obtain raw iris data; The original iris data is permuted and rearranged to obtain rearranged iris data; Set the block bit width, and divide the rearranged iris data into multiple data blocks equally according to the block bit width; The binary data in the multiple data blocks is converted into decimal data to obtain multiple decimal iris data; Based on the block bit width, and using the decimal standard value calculation formula, the decimal standard value is obtained. The decimal standard value calculation formula is as follows: ;in, b is the decimal standard value, and b is the block bit width; The magnitudes of the plurality of decimal iris data and the decimal standard value are determined sequentially. When the decimal iris data is greater than the decimal standard value, the corresponding inverted and merged iris data is determined based on the inversion formula, which is: ;in, For the inverted and merged iris data, The decimal iris data; When the decimal iris data is not greater than the decimal standard value, the decimal iris data is determined to be the corresponding inverted and merged iris number; The inverted and merged iris data is grouped to obtain multiple data groups, and each of the multiple data groups is sorted to obtain a sorted sequence of the inverted and merged iris data. The sorted sequence is then determined to be the encrypted data of the original iris data.

2. The iris data privacy protection method according to claim 1, characterized in that, The process of permuting and rearranging the original iris data to obtain rearranged iris data includes: Obtain a random permutation string, wherein 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 are not repeated; Based on the random permutation string, the original iris data is permuted and rearranged to obtain rearranged iris data.

3. The iris data privacy protection method according to claim 1, characterized in that, The process of grouping the inverted and merged iris data into multiple data groups, sorting each of the multiple data groups to obtain a sorted sequence of the inverted and merged iris data, and determining the sorted sequence as the encrypted data of the original iris data includes: Set the group width, and divide the inverted and merged iris data into multiple data groups according to the group width; According to the size of the data value, the inverted and merged iris data in the multiple data groups are sorted to obtain multiple sorting sequences corresponding to the multiple data groups; The sorted sequence is determined to be encrypted data of the original iris data.

4. An iris data recognition method, characterized in that, include: Retrieve encrypted data from the database; The iris data encryption method is used to obtain the encrypted data to be authenticated based on the iris data encryption method, wherein the iris data encryption method is the step in the iris data encryption method according to any one of claims 1-3 above; According to the Hamming distance calculation formula, the Hamming distance between the encrypted data to be authenticated and the encrypted data in the database is calculated respectively to obtain the authentication distance; Set a distance threshold; When the distance to be authenticated is not greater than the distance threshold, the iris data to be authenticated is determined to be successfully authenticated.

5. The iris data recognition method according to claim 4, characterized in that, The Hamming distance calculation formula is as follows: in, The Hamming distance, Encrypt the data to be authenticated The i-th block in The i-th block of the encrypted data d in the database is encrypted, where the value of i ranges from [1, 10×m], and m is the total number of data blocks.

6. An electronic device, characterized in that, The device includes a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it implements the iris data privacy protection method as described in any one of claims 1-3, or the iris data recognition method as described in any one of claims 4-5.

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