A data intelligent protection method and system for preventing access card from being lost

Abstract

The present application relates to the field of data encryption protection, and proposes a data intelligent protection method and system for an anti-loss access card, including: encoding the data to be protected in the anti-loss access card to obtain a plaintext character sequence; determining the level requirement based on the similarity between the character string and its neighboring character string in all cluster center points contained in the parent node segmentation value of the cluster to which it belongs; determining the easy association degree based on the attraction of the cluster cluster to the character strings in the remaining clusters contained in the parent node segmentation value; determining the protection level coefficient based on the level requirement and the easy association degree; generating round keys based on the protection level coefficients corresponding to the adjacent character strings in the plaintext character sequence; and saving the plaintext group and the ciphertext group compressed by the plaintext group to each sector in the anti-loss access card. The present application reduces the probability of decipherability between the round keys generated by fixed directions and fixed displacement lengths, and realizes the intelligent protection of the data of the anti-loss access card.

Description

Technical Field

[0001] The present application relates to the field of data encryption protection, and in particular to a method and system for intelligently protecting data of an access control card against loss. Background Art

[0002] Access cards are electronic devices used for identity verification. They are used in conjunction with electronic access control systems to ensure that only people with specific permissions can enter restricted buildings or areas, thereby achieving access control to restricted areas. Access cards with positioning functions can store information such as user ID, permission level, and valid time period, and can also obtain location information to prevent the carrier from losing it and facilitate retrieval.

[0003] The current access control system can set different permission levels for different behaviors, different time periods, different locations and other factors, and limit the access rights of different users' access control cards. In this way, even if the access control card is lost or stolen, it is not easy to enter the area controlled by the access control system. The data protection of the anti-loss access control card is mainly achieved by encrypting the access control card data, and the community is responsible for the management and maintenance of the access control system to improve the security of the access control card and better protect the access control card data. When protecting the data of the anti-loss access control card, the protection effect mainly depends on the structural design of the 16 sectors of the anti-loss access control card and the security encryption mechanism.

[0004] However, since the data information in the access card can be maliciously copied and forged, and the size of the access card is often small, it is a lightweight embedded application. Therefore, at this stage, symmetric encryption or lightweight cryptographic algorithms are usually used to encrypt the access card data. For example, PRIDE algorithm, KTANTAN algorithm, Simon encryption algorithm, etc. When using lightweight encryption algorithms to encrypt and protect the data in the data blocks within the 16 sectors of the anti-loss access card, due to the defects of secret key expansion, there is a greater risk of ciphertext being cracked. It is necessary to select a suitable key with appropriate length to improve the security of the anti-loss access card data. Summary of the invention

[0005] The present application provides an intelligent data protection method and system for preventing access control cards from being lost, in order to solve the problem of high decipherability and low security when round keys generated in a fixed manner encrypt access control data. The technical solutions adopted are as follows:

[0006] In a first aspect, an embodiment of the present application provides a method for intelligently protecting data of an access card against loss, the method comprising the following steps:

[0007] Acquire the data to be protected and determine the plaintext character sequence of the data to be protected, wherein the data to be protected is any data that can be read from the access control card in the access control system;

[0008] The plaintext character sequence is divided into strings of length 4 bytes, and the level requirement of each string is determined based on the similarity between each string and its neighboring strings between all cluster center points contained in the parent node segmentation value of the cluster to which it belongs;

[0009] Determine the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of each cluster to the character string contained in the remaining clusters of the parent node segmentation value; determine the protection level coefficient of each cluster based on the level requirement of the character string and the easy association degree;

[0010] Determine a single secret key string for each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence;

[0011] Determine the label value of a single key string based on the protection level coefficient of the cluster where each string is located and the protection level coefficients of the clusters where two adjacent strings of each string are located in the plaintext character sequence, and generate a round key based on the comparison result of the label value of the single key string and the adjacent right key string;

[0012] The plaintext character sequence is encrypted based on the round key, and the plaintext group and the ciphertext group compressed from the plaintext group are saved in each sector.

[0013] In the above scheme, firstly, the data to be protected is converted into a plain text character sequence by means of data encoding, so as to facilitate the subsequent evaluation of the security requirements of different content data; secondly, the strings of the same length are processed by clustering based on the similarity measurement distance between the strings, and the cluster to which each string belongs and the parent node segmentation value of each cluster are determined to obtain the level requirement of each string; then, according to the degree of similarity between each cluster and the strings in the remaining clusters contained in its parent node segmentation value, the degree of attraction of each cluster to the strings in the remaining clusters contained in its parent node segmentation value is judged, and the degree of easy association of the access control data information corresponding to each cluster is determined based on the degree of attraction, and the level requirement of each cluster is determined in combination with all the strings in each cluster. The protection level coefficient of the cluster cluster; further, the key stream is obtained based on the randomly generated hyperchaotic sequence segmentation, and a mapping value is assigned to each cluster cluster in an iterative manner based on the protection level coefficients of all cluster clusters and the chaotic mapping function, and the two key streams are nonlinearly transformed using the protection level coefficient and the mapping value to obtain the first round of the secret key string sequence; further, the access control data importance of each string is calculated based on the importance of the data corresponding to each string, and the label value of each single secret key string is obtained, and the round key is generated based on the comparison result of the label value of the single secret key string in the first round of the secret key string sequence and the adjacent right secret key string; finally, the plaintext character sequence is divided into multiple plaintext groups, and a secret key string sequence is assigned to the encryption key of a plaintext group to complete the encryption protection of the plaintext character sequence.

[0014] In summary of the first aspect, in some possible implementations, determining the level requirement of each string based on the similarity between each string and its neighboring strings in all cluster center points included in the parent node segmentation value of the cluster to which it belongs includes:

[0015] Taking all the strings as input, using a hierarchical clustering algorithm to obtain clustering results of the strings, and determining the parent node segmentation value of each cluster cluster based on the clustering results;

[0016] Get the neighboring strings of each string, and take the sequence consisting of the measured distances between each string and all cluster center points contained in the parent node segmentation value of the cluster to which it belongs in ascending order as the distance sequence of each string;

[0017] Performing similarity measurement on the distance sequence between each character string and any of the neighboring character strings to obtain multiple measurement results, and taking the sum of all the measurement results as the first eigenvalue of each character string;

[0018] Determine the degree of discreteness of the measured distance between each string and all neighboring strings of each string and the center point of the cluster where the string is located;

[0019] The level requirement of each character string consists of two parts: the first characteristic value and the discrete degree, wherein the level requirement is positively correlated with the first characteristic value and the discrete degree respectively.

[0020] In the above scheme, strings with different data contents are divided into multiple clusters through a hierarchical clustering algorithm; the possibility that each string corresponds to different content data is judged by the similarity between each string and the corresponding strings of different cluster centers, and the encryption level required for each string is accurately evaluated by the level requirement of each string.

[0021] In summary of the first aspect, in some possible implementations, determining the parent node segmentation value of each cluster based on the clustering result includes:

[0022] In the hierarchical clustering process, when each cluster is treated as a cluster cluster, the upper cluster cluster where the previous split is located is used as the parent node split value of each cluster cluster.

[0023] In the above scheme, the parent node segmentation value is determined by the number of segmentation times corresponding to each cluster in the hierarchical clustering process, and the correlation between the string in each cluster and the remaining strings is evaluated by the upper clusters and lower clusters between different clusters in the clustering space. At the same time, the impact of the differences in data structure caused by the different types of data that actually need to be protected on subsequent group encryption can be eliminated.

[0024] In summary of the first aspect, in some possible implementations, the determination of the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of each cluster to the character strings in the remaining clusters contained in the segmentation value of the parent node to which it belongs includes:

[0025] Calculate the mean of the measured distances between the string corresponding to each cluster center and the remaining strings in the clusters contained in the parent node segmentation value of each cluster as the first mean;

[0026] The product of the number of clusters contained in the segmentation value of each cluster parent node and the number of strings in each cluster is used as the first weight;

[0027] The easy association degree of the access control data information corresponding to each cluster consists of two parts: a first weight and a first mean value, wherein the easy association degree is positively correlated with the first weight, and the easy association degree is negatively correlated with the first mean value.

[0028] In the above scheme, the correlation between the data content in each cluster and the data content in the remaining clusters is evaluated by the attraction of the center point of each cluster to the strings in the remaining clusters contained in the segmentation value of its parent node, so as to improve the degree of distinction between strings in different clusters.

[0029] In summary of the first aspect, in some possible implementations, the method for determining the protection level coefficient of each cluster based on the level requirement of the character string and the easy association degree is:

[0030] Calculate the mean of the rank requirements of all strings in each cluster;

[0031] The protection level coefficient of each cluster consists of the mean value and the degree of easy association of the access control data information corresponding to each cluster. The protection level coefficient is negatively correlated with the mean value and the degree of easy association respectively.

[0032] In the above scheme, by analyzing the number of strings in each cluster and the similarity between the remaining strings in the cluster contained in the parent node segmentation value, the degree of correlation between the data content corresponding to the strings in different clusters is accurately evaluated; and by judging whether the cluster contains strings formed by local repeated data in different types of access control data through the protection level coefficient, the security requirements of the data corresponding to each cluster are accurately evaluated.

[0033] In summary of the first aspect, in some possible implementations, determining a single secret key string for each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence includes:

[0034] A hyperchaotic sequence is randomly generated by using a chaotic map, and the hyperchaotic sequence is divided into two initial key streams, wherein the division is divided from any non-endpoint position in the hyperchaotic sequence;

[0035] The mean value of the protection level coefficients of all clusters is used as the segmentation threshold of the Tent chaotic mapping function to determine the mapping formula; multiple mapping values ​​are iteratively generated using the mapping formula, and a mapping value is randomly assigned to each cluster;

[0036] The protection level coefficient and mapping value of each cluster are used as a coefficient respectively, and nonlinear transformation is performed on the two initial key streams. The result of the nonlinear transformation is used as a single secret key string of each cluster.

[0037] In the above scheme, the hyperchaotic sequence is divided into two initial key streams by random segmentation to improve the randomness and difference of the initial key streams; secondly, a mapping value is assigned to each cluster cluster in an iterative manner, and the two initial key streams are nonlinearly transformed based on the protection level coefficient and mapping value of each cluster cluster to improve the distinguishability between the obtained secret key strings.

[0038] In summary of the first aspect, in some possible implementations, determining the label value of a single key string based on the protection level coefficient of the cluster where each string is located and the protection level coefficients of the clusters where two adjacent strings of each string are located in the plaintext character sequence includes:

[0039] Respectively calculating the absolute values ​​of the differences between the protection level coefficient of the cluster where each character string is located and the protection level coefficients of the clusters where the two adjacent characters to the left and right of each character string are located in the plain text character sequence, and taking the sum of the absolute values ​​of the differences as the first difference;

[0040] The access control data importance of each string is composed of two parts: the first difference and the protection level coefficient of the cluster where each string is located, wherein the access control data importance is positively correlated with the first difference and the protection level coefficient of the cluster where each string is located;

[0041] The sum of the access control data importance of all strings in the cluster corresponding to each single secret key string is used as the label value of each single secret key string.

[0042] In the above scheme, the importance of the data corresponding to each string is evaluated by the difference in the encryption level requirements of adjacent strings in the plaintext character sequence and the encryption level required by the cluster where each string is located, so that different access control data importance can be given to data with different privacy.

[0043] In summary of the first aspect, in some possible implementations, generating a round key based on a comparison result of the label value of the single key string and its adjacent right key string includes:

[0044] The sequence of single secret key strings of all clusters is used as the secret key string sequence of the first round;

[0045] S1: Determine the comparison result of the label value of each single key string in the first round of key string sequence and the adjacent key string on the right;

[0046] S2: determining the displacement length of each single secret key string based on the comparison result, and determining the key string of the second round corresponding to each single secret key string in the secret key string sequence of the first round based on the displacement length;

[0047] S3: traverse a single secret key string in the secret key string sequence of the first round, and use the sequence of key strings obtained as the key string sequence of the second round;

[0048] S4: Based on the comparison result of the label value of each single key string in the second round of key string sequence with the adjacent key string on the right, repeat steps S2 and S3.

[0049] In the above scheme, the displacement length and displacement direction of each single secret key string are determined based on the comparison result of the label value of each single secret key string with the adjacent single secret key string on the right, so that the direction and length of different single secret key strings when generating the next round of secret key strings are in an unfixed state, thereby reducing the probability of deciphering the round keys generated by fixed directions and fixed displacement lengths, and improving the security of access control data encryption.

[0050] In summary of the first aspect, in some possible implementations, encrypting the plaintext character sequence based on the round key and saving the plaintext group and the ciphertext group compressed from the plaintext group to each sector includes:

[0051] The plaintext character sequence is used as the input of the block encryption algorithm, the plaintext character sequence is divided into a preset number of plaintext groups, the secret key string sequence of each round is used as the encryption key of each plaintext group, and the ciphertext group of each plaintext group is obtained;

[0052] Each ciphertext group is compressed, and the compressed ciphertext group and the plaintext group are placed in a sector in the access control card storage space.

[0053] In the above scheme, the plaintext character sequence is encrypted by block encryption, which improves the encryption efficiency; the compression of the ciphertext group enables the ciphertext group and the plaintext group to be stored in the sector without the need for additional storage space, thereby improving data security and avoiding resource waste.

[0054] In a second aspect, a data intelligent protection system for preventing loss of access control cards is provided, the system comprising:

[0055] An acquisition module, used to acquire the data to be protected and determine a plain text character sequence of the data to be protected, wherein the data to be protected is any data that can be read from an access control card in the access control system;

[0056] A classification module is used to divide the plain text character sequence into strings of 4 bytes in length, and determine the level requirement of each string based on the similarity between each string and all cluster center points contained in the parent node segmentation value of the cluster to which it belongs with its neighboring strings;

[0057] A calculation module is used to determine the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of each cluster to the character strings in the remaining clusters contained in the parent node segmentation value; and determine the protection level coefficient of each cluster based on the level requirement of the character string and the easy association degree;

[0058] A determination module, used for determining a single secret key string of each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence;

[0059] A generation module, used to determine the label value of a single secret key string based on the protection level coefficient of the cluster where each string is located and the protection level coefficients of the clusters where two adjacent strings of each string are located in the plaintext character sequence, and generate a round key based on the comparison result of the label value of the single secret key string and the secret key string adjacent to the right;

[0060] The protection module is used for storing the plaintext group and the ciphertext group compressed from the plaintext group in each sector.

[0061] In a third aspect, a server is provided, comprising a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the method in the first aspect or any possible implementation of the first aspect.

[0062] In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation manner of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0064] Figure 1 A flowchart of an intelligent data protection method for preventing access card loss provided by an embodiment of the present application;

[0065] Figure 2 A schematic diagram of an implementation environment for an intelligent data protection method for preventing access control cards from being lost provided by an embodiment of the present application;

[0066] Figure 3 A flowchart for implementing the string level requirement provided by one embodiment of the present application;

[0067] Figure 4 A schematic diagram of a parent node segmentation value provided by an embodiment of the present application;

[0068] Figure 5 An implementation flow chart of the protection level coefficient of each cluster provided by an embodiment of the present application;

[0069] Figure 6 This is a flowchart of the implementation of round key generation provided in one embodiment of the present application;

[0070] Figure 7 A schematic diagram of a plaintext character sequence group encryption provided by an embodiment of the present application;

[0071] Figure 8 A schematic diagram of the structure of an intelligent data protection system for preventing access card loss provided by an embodiment of the present application;

[0072] Fig. 9 A schematic diagram of the structure of a computer device provided in accordance with an embodiment of the present application. DETAILED DESCRIPTION

[0073] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0074] The technical solution in the present application will be described clearly and in detail below in conjunction with the accompanying drawings. In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0075] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0076] The following is an introduction to the technical solution provided by the embodiment of the present application. An embodiment of the present application provides a data intelligent protection method for preventing the loss of access control cards. Figure 1 , which shows a flow chart of a data intelligent protection method for an anti-loss access card provided by an embodiment of the present application, the method comprising the following steps:

[0077] 101. Obtain the data to be protected and determine the plaintext character sequence of the data to be protected.

[0078] At present, the mainstream anti-loss access control cards usually use M1 cards. The basic data structure inside the anti-loss access control card is divided into 16 sectors. When making the anti-loss access control card, a specific function will be set for each sector. The storage space of the anti-loss access control card is usually divided into 16 sectors, corresponding to 16 numbers from 0 to 15. Each sector is divided into 4 storage units with serial numbers 0 to 3. The first 3 storage units of each sector are used to store data, and the last storage unit is used as a control unit. The first 6 bytes store the password, the middle 4 bytes are the control field, and the last 6 bytes store another password.

[0079] It should be noted that in this application, the intelligent data protection of the anti-loss access card is determined by the user, such as a community, office building, etc., to determine the data content that needs to be protected in the access control system, and then encrypt the data in the anti-loss access card for protection. Since the data stored in each sector is different, in this application, the protected data that needs to be encrypted in the anti-loss access card is obtained from the user's access control system. In this application, the data to be protected can be any data that needs to be encrypted and protected that can be placed in the storage space of the access card, including but not limited to the identification number UID, permission information, personal data, or transaction data. The specific data to be protected can be selected by the implementer according to the usage scenario of the access control system.

[0080] Secondly, the data to be protected is encoded using UTF-8, and the sequence composed of the encoding results is used as the plain text character sequence of the data to be protected in the anti-loss access control card. UTF-8 encoding is a well-known technology, and the specific process will not be repeated here.

[0081] It should be noted that this embodiment only provides one encoding method, that is, UTF-8 encoding is performed on the protected data. Under the premise that the data encoding can be implemented to obtain a plain text character sequence, in other embodiments, other encoding methods may also be selected for encoding.

[0082] 102 , determining the level requirement of each character string based on the similarity between each character string and its neighboring character strings in all cluster center points included in the parent node segmentation value of the cluster to which it belongs.

[0083] The following first introduces the implementation environment of the embodiment of the present application. Figure 2As shown, the implementation environment of the data intelligent protection method for preventing the loss of access control cards provided in the embodiment of the present application includes a data acquisition terminal 201, a server 202, a data encryption terminal 203, and a protection terminal 204. The data acquisition terminal 201 and the server 202, the server 202 and the data encryption terminal 203 are connected through a wireless network, and the protection terminal 204 is connected to the data encryption terminal 203 through a wireless or wired network. The data acquisition terminal 201 can be any type of terminal, for example, an access control integrated machine, a card reader. The data collection terminal 201 collects the data to be protected and uploads it to the server 202; the server 202 encodes the data to be protected into a plaintext character sequence, divides the plaintext character sequence into strings of 4 bytes in length, and determines the level requirement of each string based on the similarity between each string and its neighboring strings between all cluster center points contained in the parent node segmentation value of the cluster to which it belongs; determines the easy association degree of the access control data information corresponding to each cluster based on the degree of attraction of each cluster to the strings in the remaining clusters contained in the parent node segmentation value; determines the protection level coefficient of each cluster based on the level requirement of the string and the easy association degree; the data collection terminal 201 sends the plaintext character sequence to the data encryption terminal 203, and the server 202 sends the protection level coefficients of all clusters to the data encryption terminal 203, The data encryption end 203 determines a single secret key string for each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence, determines a label value of the single secret key string based on the protection level coefficient of the cluster where each character string is located and the protection level coefficient of the cluster where the two adjacent character strings of each character string are located in the plaintext character sequence, generates round keys based on the comparison result of the label values ​​of the single secret key string and the secret key string adjacent to the right, and obtains the key string sequence of each round. The data encryption end 203 sends the key string sequence of each round to the protection end 204, and the protection end 204 assigns a secret key string sequence to each plaintext group, encrypts the plaintext character sequence in the form of block encryption, obtains a ciphertext group for each plaintext group, compresses each ciphertext group, and puts the compressed ciphertext group and plaintext group into the sector in the access control card storage space.

[0084] Server 202 is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, distribution networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0085] The level requirement of each string is used to characterize the degree of security encryption level requirement of the data corresponding to each string. The lower the level requirement of the string, the more likely the data content corresponding to each string in the plaintext character sequence is to be data with a low authority level and weak privacy; the higher the level requirement of the string, the more likely the data content corresponding to each string in the plaintext character sequence is to be data with a high authority level and the type of data that carries personal privacy information and requires high-level encryption protection. In the present application, the level requirement of each string in each cluster is determined based on the degree of difference and attraction between the strings in the clustering results of the strings divided by the plaintext character sequence. In one embodiment of the present application, obtaining the level requirement of each string can be achieved by the following process, such as Figure 3 As shown, the above step 102 can be implemented by the following steps 301 and 302:

[0086] 301, clustering the plain text character sequence, and determining the parent node segmentation value of each cluster and the neighboring character strings of each character string.

[0087] For the same user, some basic functions of different anti-loss access cards are the same, such as regional access, etc. Regardless of whether it is the property or the owner, the access card of the carrier who can normally enter and exit the community has access rights to the access control system, and the corresponding data does not require a very high encryption level. However, data that is highly related to the carrier's personal privacy information, such as the carrier's information, fees, access rights, etc., which are the main objects of malicious copying, should be encrypted at a higher level and with more complex secret keys in the anti-loss access card.

[0088] Since the capacity of each storage unit is 16 bytes, in order to perform fine-grained analysis on the plaintext character sequence of the data to be protected in the anti-loss access control card, the plaintext character sequence of the data to be protected in the anti-loss access control card is divided into strings of equal lengths of 4 bytes.

[0089] It should be noted that if the length of the plain text character sequence of the data to be protected in the anti-loss access control card is not an integer multiple of 4, the last remaining characters are padded with zeros to make the length of each character string 4 bytes.

[0090] Furthermore, the difference measurement results between all strings are used as the metric distance for clustering, all strings are used as input, and all strings are divided into different clusters using a hierarchical clustering algorithm. The difference measurement results are calculation results that can evaluate the difference between two strings, including but not limited to Levenshtein distance and ED edit distance. And among all strings, the k nearest neighbor algorithm is used to obtain the k nearest neighbor strings of each string in each cluster. Among them, the hierarchical clustering algorithm and the k nearest neighbor algorithm are both well-known technologies, and the specific process will not be repeated.

[0091] Secondly, since the data types with different privacy and security requirements are different but the content is the same, some bytes of the corresponding strings will be the same, which will interfere with the subsequent evaluation of the protection level required for each string.

[0092] In the clustering results, the fewer the number of splits corresponding to each cluster as a cluster, the higher the degree of data independence of each cluster. When each cluster is treated as a cluster, the upper cluster where the previous split is located is used as the parent node split value of each cluster, such as Figure 4 As shown, the horizontal and vertical axes are the string order value and the segmentation value, respectively. The black circle represents the cluster, and the gray circle represents the other clusters contained in the segmentation value of the parent node of the cluster.

[0093] It should be noted that the beneficial effect of determining the parent node split value is that by evaluating the correlation between the string in each cluster and the remaining strings through the upper clusters and lower clusters between different clusters in the cluster space, it can eliminate the impact of the differences in data structure caused by the different types of data that actually need to be protected on subsequent group encryption.

[0094] 302 , determining the level requirement of each character string based on the metric distance between each character string and its neighboring character strings to the same parent node segmentation value.

[0095] Data with a high correlation with the personal privacy information of the anti-loss access card carrier is usually set according to the permissions, functions and personal access behaviors required by the carrier. The local density of the corresponding character string in the clustering space should be small, and the sensitivity of the data is high. That is, the higher the probability that the string obtained by segmenting the plaintext character sequence of the data to be protected in the anti-loss access card contains sensitive information, the higher the encryption level required, and the higher the crackability of the corresponding ciphertext.

[0096] For each string, the sequence of the measured distances between each string and all the cluster centers contained in the parent node segmentation value of the cluster to which it belongs is taken as the distance sequence of each string, and the similarity is measured for the distance sequence between each string and any of its neighboring strings, and k measurement results are obtained, and the sum of all measurement results is taken as the first eigenvalue of each string. The measurement results are used to evaluate the similarity between the distance sequence of the string and the distance sequence of the neighboring strings. The higher the similarity, the more similar the data content between each string and its neighboring strings. Therefore, the measurement results can be represented by similarity measurement indicators including but not limited to the Pearson correlation coefficient between the distance sequences and the largest common subsequence.

[0097] Furthermore, the level demand of each string is composed of two parts: the first eigenvalue of each string and the discrete degree of the measured distance between each string and all neighboring strings of each string and the center point of the cluster where each string is located. The level demand is positively correlated with the first eigenvalue and the discrete degree respectively. In one embodiment, the calculation relationship between the easy association degree A1 and the first weight B1 and the first mean C1 is: The discrete degree is used to reflect the degree of attraction of the cluster center of the cluster where the neighboring strings of each string are located to each string. The higher the attraction, the more conventional the data content corresponding to each string is, and the less important it is in the access card data; the more likely the string is to correspond to access control data with a low authority level and a high similarity, the lower the requirement for the encryption level.

[0098] It should be noted that the degree of discreteness is obtained by the distribution of the metric distances between each string and all neighboring strings of each string and the center point of the cluster where each string is located. In one embodiment, the distribution variance of the metric distance may be calculated; in other embodiments, the coefficient of variation of the metric distance may also be calculated. This application does not impose any special limitation on the method for calculating the degree of discreteness.

[0099] It should be understood that a positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. The specific relationship can be an additive relationship, a multiplicative relationship, etc., which is determined by actual application and is not specifically limited in this application.

[0100] 103, based on the attraction of each cluster cluster to the string in the remaining cluster clusters contained in the parent node segmentation value, determine the easy association degree of the access control data information corresponding to each cluster cluster; based on the level requirement of the string and the easy association degree, determine the protection level coefficient of each cluster cluster. The protection level coefficient of each cluster cluster is used to characterize the intra-cluster stability of each cluster cluster. The larger the protection level coefficient, the higher the intra-cluster stability, the more likely the cluster cluster is a cluster cluster corresponding to the string formed by local repeated data in different types of access control data, the smaller the impact on the data security in the anti-loss access control card, and a lower level of encryption protection can be performed; the smaller the protection level coefficient, the worse the intra-cluster stability, the more likely the cluster cluster is a cluster cluster of string clusters formed by the same type of data with strong privacy, the greater the impact on the data security in the anti-loss access control card, and a high level of encryption protection should be performed. In this application, the protection level coefficient of each cluster cluster is determined based on the level requirement of each string and the attraction of each cluster cluster center to the string in the remaining cluster clusters contained in the parent node segmentation value.

[0101] Through the processing of the above steps, the level requirement of each character string is obtained, and for the data to be protected in the anti-loss access control card, the level requirement can be used to evaluate the importance of the part of the data to be protected in the anti-loss access control card corresponding to each character string to the user, and in the fan-shaped area, the stored data is usually point data level data. Therefore, when encrypting the data to be protected in the anti-loss access control card, it is necessary to further consider multiple similar character strings, that is, the importance of the data to be protected corresponding to each cluster to the user of the anti-loss access control card.

[0102] In one embodiment of the present application, obtaining the protection level coefficient of each cluster can be achieved through the following process: Figure 5 As shown, the above step 103 can be implemented by the following steps 501 and 502:

[0103] 501 , determining the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of the different cluster centers contained in the parent node segmentation value to the non-center character string.

[0104] The degree of easy association of the access control data information corresponding to each cluster cluster represents the probability of associating the data information corresponding to the string in each cluster cluster with the data information corresponding to the string in different cluster clusters contained in the parent node segmentation value. The greater the degree of easy association, the higher the degree of attraction of the center point of the cluster cluster to the string in the cluster contained in its parent node segmentation value; the smaller the degree of easy association, the lower the degree of attraction of the center point of the cluster cluster to the string in the cluster contained in its parent node segmentation value, and the more likely the data content corresponding to the string in the cluster cluster is personalized data closely related to the user of the anti-loss access control card.

[0105] In the present application, the data difference between the strings is evaluated based on the metric distance between the strings in different clusters contained in the parent node segmentation value of the string corresponding to each cluster center. Specifically, the mean of the metric distances between the string corresponding to each cluster center and the strings in the remaining clusters contained in the parent node segmentation value of each cluster is calculated as the first mean.

[0106] Secondly, the number of strings in each cluster and the number of clusters contained in the parent node segmentation value of each cluster are taken as the first weight of each cluster; the more clusters under the parent node segmentation value, the smaller the distinction between multiple clusters under certain clustering condition constraints, and the more strings a cluster has, the higher the degree of attraction to the strings in different clusters contained in the parent node segmentation value, and the larger the first weight.

[0107] Furthermore, the first weight and the first mean of each cluster are used to form the easy association degree of the access control data information corresponding to each cluster, wherein the easy association degree is positively correlated with the first weight, and the easy association degree is negatively correlated with the first mean. In one embodiment, the calculation relationship between the easy association degree A2 and the first weight B2 and the first mean C2 is: .

[0108] It should be understood that a positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. The specific relationship may be an additive relationship, a multiplicative relationship, etc.; a negative correlation means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It may be a negative relationship, a division relationship, etc. The specific calculation method is determined by the actual application, and this application does not impose any special restrictions.

[0109] 502 : Determine the protection level coefficient of each cluster based on the level requirement of the character string in each cluster and the easy association degree of each cluster.

[0110] For each cluster, calculate the mean of the level requirements of all strings in each cluster, and use the size of the mean to reflect the security level required for the data to be protected corresponding to all strings in each cluster; secondly, determine the protection level coefficient of each cluster by the degree of easy association of each cluster and the mean. The protection level coefficient of each cluster consists of the mean and the degree of easy association of the access control data information corresponding to each cluster, wherein the protection level coefficient is negatively correlated with the mean and the degree of easy association, respectively. In one embodiment, the calculation relationship between the protection level coefficient A3 and the mean B3 and the degree of easy association A2 is: .

[0111] 104. Determine a single secret key string for each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence.

[0112] Here, the hyperchaotic sequence can be any hyperchaotic sequence randomly generated by using a hyperchaotic map, and the chaotic map includes but is not limited to a Logistics map and a Chebyshev map; the production of the hyperchaotic sequence is a well-known technology, and the specific process will not be repeated. Afterwards, the hyperchaotic sequence is divided from any non-endpoint position to obtain two initial key streams A and B, wherein the non-endpoint position refers to any position that does not contain the first element and the last element in the hyperchaotic sequence. Secondly, in order to facilitate subsequent block encryption and ensure that the length of the round key of each round is consistent, if the initial key streams A and B are of unequal length, the initial key stream with the longest sequence length is used as the standard, and zeros are padded at the end of the initial key stream with the shortest sequence length until the lengths of the initial key streams A and B are equal.

[0113] It should be noted that when encrypting the data to be protected in the anti-loss access control card, not only the size of the anti-loss access control card should be taken into consideration, but also the different data to be protected when the access control card is used by the user. The hyperchaotic sequence has the characteristics of large key space and a wide variety of encrypted data types. It is suitable for different types of data in the anti-loss access control card, such as user names and photos.

[0114] In one embodiment, the process of obtaining a single key string for each cluster is as follows:

[0115] S001, firstly, a weighted coefficient with strong randomness is generated for each cluster based on the protection level coefficients of all clusters, the mean of the protection level coefficients of all clusters is used as the segmentation threshold of the Tent chaotic mapping function, and the obtained Tent chaotic mapping segmentation function is used as the mapping formula in this scheme;

[0116] S002, the number of clusters obtained by hierarchical clustering of the statistical character string is recorded as N, and the mapping formula is used to perform N iterations to obtain N highly random mapping values. The purpose of such iteration is to ensure that each of the N clusters can be assigned to a mapping value. Tent chaotic mapping is a well-known technology, and the specific process will not be repeated here.

[0117] S003, using the protection level coefficient of each cluster and the mapping value of each cluster as two coefficients, performing nonlinear transformation on the initial key streams A and B, and using the result of the nonlinear transformation as a single secret key string for each cluster. Performing nonlinear transformation can reduce the security impact caused by the decrease in randomness due to excessive iterations during the generation of the initial key streams A and B. Nonlinear transformation is a well-known technology, and the specific process will not be repeated.

[0118] It should be noted that the implementation method of nonlinear transformation is not fixed. The formula of nonlinear transformation includes but is not limited to polynomial, exponential function, logarithmic function. The calculation formula of nonlinear transformation is determined by actual application and this application does not impose any special restrictions.

[0119] 105. Determine the label value of a single secret key string based on the protection level coefficient of the cluster where each character string is located and the protection level coefficients of the clusters where two adjacent character strings of each character string are located in the plaintext character sequence, and generate a round key based on the comparison result of the label value of the single secret key string and the secret key string adjacent to the right.

[0120] The generation of round keys is based on the first round of key string sequence according to a certain cycle iteration. is composed of a single key string permutation of all clusters, ,in, , , They are the single key strings of the first cluster, the second cluster, and the Nth cluster, respectively. The loop iteration is determined based on the tag value of the single key string. The larger the tag value, the greater the possibility that the single key string corresponds to a string of data with strong privacy for the anti-loss access card carrier in the cluster, and the higher the security requirement; the smaller the tag value, the lower the possibility that the single key string corresponds to a string of data with strong privacy for the anti-loss access card carrier in the cluster, and the lower the security requirement. In one embodiment of the present application, the generation of round keys can be achieved through the following process, such as Figure 6 As shown, the above step 105 can be implemented by following the steps 601 and 602:

[0121] 601, determine the label value of a single secret key string based on the protection level coefficients of the clusters to which adjacent character strings in the plain text character sequence belong.

[0122] For each string, obtain the two strings adjacent to each string on the left and right in the plaintext string sequence, calculate the absolute value of the difference between the protection level coefficient of the cluster where each string is located and the protection level coefficient of the cluster where the two adjacent strings are located, and take the sum of the two absolute values ​​as the first difference. If a string has only one adjacent string, take the absolute value of the difference between the protection level coefficient of the cluster where this string is located and the protection level coefficient of the cluster where the only adjacent string is located as the first difference. The first difference reflects the privacy difference of the data content between each string and the adjacent string. The larger the first difference, the greater the difference in the security protection level required for the data content corresponding to each string and its adjacent string, that is, there may be a situation in the data to be protected that is close in position but has a large difference in content. For example, the unit numbers of different anti-loss access control card carriers may be repeated, but the household numbers will not be repeated. The security requirement is high, and the protection level coefficients of the clusters where the adjacent strings corresponding to the unit number and the household number are located are relatively different.

[0123] Secondly, the access control data importance of each string is determined based on the first difference and the protection level coefficient of the cluster where each string is located. The access control data importance consists of the first difference and the protection level coefficient of the cluster where each string is located. The access control data importance is positively correlated with the first difference and the protection level coefficient of the cluster where each string is located. In one embodiment, the access control data importance V is positively correlated with the first difference D and the protection level coefficient of the cluster where each string is located. The calculation relationship is: .

[0124] Further, The sum of the importance of access control data of all strings in the cluster corresponding to each single secret key string is taken as the label value of each single secret key string.

[0125] 602, based on the comparison result of the label value of a single key string in the key string sequence of the previous round, a key string sequence of the next round is generated.

[0126] Based on the comparison result of the label value of each single key string in the first round of the key string sequence and its adjacent right key string, the shift is performed. Specifically, if the label value of the single key string is greater than the label value of the adjacent key string on the right, the product of the rounded result of the difference between the two label values ​​and 16 is calculated as the shift length L, the single key string is shifted to the right by L bits, and the shift result is used as the key string of the second round corresponding to the single key string, and the product of the rounded result of the difference and the label value of the single key string is used as the label value of the second round of the key string; if the label value of the single key string is less than or equal to the label value of the adjacent key string on the right, the average of the single key string and any other single key string is selected as the key string of the second round, and the average of the label values ​​of the two key strings is used as the label value of the key string of the second round. For the last single key string in each round of the key string sequence, the last single key string is compared and shifted with the first single key string in the above manner.

[0127] Traverse the first round of secret key string sequence, and use the sequence of the second round of secret key strings generated in sequence as the second round of secret key string sequence , which is the round key of the second round. This way of obtaining the round key can reduce the probability of deciphering the round keys generated by fixed directions and fixed displacement lengths, and improve the security of access control data encryption.

[0128] Furthermore, the above process is repeated until multiple rounds of secret key string sequences are obtained.

[0129] 106 , encrypt the plaintext character sequence based on the round key, and save the plaintext group and the ciphertext group compressed from the plaintext group to each sector.

[0130] In the present application, the plaintext character sequence is encrypted in groups, and the encryption efficiency and security are improved by group encryption.

[0131] Specifically, the plaintext character sequence is used as the input of the block encryption algorithm, and the plaintext character sequence is divided into M plaintext groups. According to the method in 105 above, the M rounds of secret key string sequences are iteratively generated, and the secret key string sequence of each round is used as the encryption key of each plaintext group. The plaintext groups are encrypted one by one to obtain the encrypted ciphertext groups, and the length of the ciphertext group is consistent with the length of the plaintext group. The block encryption process is as follows: Figure 7 As shown, , , They are the secret key string sequences of the first round, the second round, and the Mth round respectively. M plaintext groups correspond to M secret key string sequences.

[0132] Furthermore, when intelligently protecting the data to be protected in the anti-loss access card, it is necessary to consider the sector division in the data storage space of the access card and the size of the storage space. In this application, each plaintext group and the ciphertext group corresponding to each plaintext group are compressed, and each ciphertext group is compressed into 12 bytes of ciphertext. Secondly, the plaintext group is placed in the storage unit with serial number 0-3 of each sector, and the 12 bytes of ciphertext are used as the secret key area in the control unit with serial number 4 to complete the encryption protection of the data to be protected in the anti-loss access card.

[0133] The embodiment of the present application provides a data intelligent protection system for preventing loss of access control cards, such as Figure 8 As shown, the system 800 includes:

[0134] The acquisition module 801 is used to acquire the data to be protected and determine the plain text character sequence of the data to be protected, wherein the data to be protected is any data that can be read from the access control card in the access control system;

[0135] A classification module 802 is used to divide the plain text character sequence into strings of 4 bytes in length, and determine the level requirement of each string based on the similarity between each string and all cluster center points included in the parent node segmentation value of the cluster to which it belongs with its neighboring strings;

[0136] The calculation module 803 is used to determine the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of each cluster to the character string in the remaining clusters contained in the parent node segmentation value; determine the protection level coefficient of each cluster based on the level requirement of the character string and the easy association degree;

[0137] A determination module 804 is used to determine a single secret key string for each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence;

[0138] A generation module 805 is used to determine the label value of a single key string based on the protection level coefficient of the cluster where each string is located and the protection level coefficients of the clusters where two adjacent strings of each string are located in the plaintext character sequence, and to generate a round key based on the comparison result of the label value of the single key string and the adjacent right key string;

[0139] The protection module 806 is used to save the plaintext group and the ciphertext group compressed from the plaintext group to each sector.

[0140] It should be noted that the system provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, the data intelligent protection system for anti-loss access control cards and the data intelligent protection method for anti-loss access control cards provided in the above embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0141] Fig. 9 is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. For example, Fig. 9 As shown, the computer device 900 includes: a memory 901, a processor 902, and a computer program 903 stored in the memory 901 and running on the processor 902, wherein when the processor 902 executes the computer program 903, the computer device can execute the aforementioned intelligent data protection method for preventing loss of access control cards.

[0142] In addition, an embodiment of the present application also protects a device, which may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to execute an intelligent data protection method for an anti-loss access card provided in an embodiment of the present application.

[0143] This embodiment can divide the functional modules of the device according to the above method example. For example, it can correspond to each functional module, or two or more functions can be integrated into one processing module. For example, the processing functions of string clustering and protection level coefficient in the above-mentioned data intelligent protection method for anti-lost access control cards are integrated into one data processing module. The above-mentioned integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0144] In the case of dividing each module according to each function, the device may also include a door access data upload module, a determination module, an adjustment module, etc. It should be noted that all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module, which will not be repeated here.

[0145] It should be understood that the device provided in this embodiment is used to execute the above-mentioned intelligent data protection method for preventing loss of access control cards, and thus can achieve the same effect as the above-mentioned implementation method.

[0146] In the case of an integrated unit, the device may include a processing module and a storage module. When the device is applied to a device, the processing module may be used to control and manage the actions of the device. The storage module may be used to support the device to execute mutual program codes, etc.

[0147] The processing module may be a processor or a controller, which may implement or execute various exemplary logic blocks, modules and circuits disclosed in the present application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module may be a memory.

[0148] In addition, the device provided in the embodiments of the present application may specifically be a chip, component or module, and the chip may include a connected processor and memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute an intelligent data protection method for preventing the loss of access control cards provided in the above embodiments.

[0149] This embodiment also provides a computer-readable storage medium, which stores computer program code. When the computer program code runs on a computer, the computer executes the above-mentioned related method steps to implement an intelligent data protection method for an anti-loss access card provided in the above embodiment.

[0150] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A data intelligent protection method for preventing loss of access control cards, characterized in that: The method comprises the following steps: Acquire the data to be protected and determine the plaintext character sequence of the data to be protected, wherein the data to be protected is any data that can be read from the access control card in the access control system; Divide the plaintext character sequence into strings of 4 bytes in length, and determine the level requirement of each string based on the similarity between each string and its neighboring strings between all cluster center points contained in the parent node segmentation value of the cluster to which it belongs; Determine the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of each cluster to the character string contained in the remaining clusters of the parent node segmentation value; determine the protection level coefficient of each cluster based on the level requirement of the character string and the easy association degree; Determine a single secret key string for each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence; Determine the label value of a single key string based on the protection level coefficient of the cluster where each string is located and the protection level coefficients of the clusters where two adjacent strings of each string are located in the plaintext character sequence, and generate a round key based on the comparison result of the label value of the single key string and the adjacent right key string; Encrypt the plaintext character sequence based on the round key, and save the plaintext group and the ciphertext group compressed from the plaintext group to each sector; The step of determining the level requirement of each string based on the similarity between each string and its neighboring strings among all cluster center points included in the parent node segmentation value of the cluster to which it belongs includes: Taking all the strings as input, using a hierarchical clustering algorithm to obtain clustering results of the strings, and determining the parent node segmentation value of each cluster cluster based on the clustering results; Get the neighboring strings of each string, and take the sequence consisting of the measured distances between each string and all cluster center points contained in the parent node segmentation value of the cluster to which it belongs in ascending order as the distance sequence of each string; Performing similarity measurement on the distance sequence between each character string and any of the neighboring character strings to obtain multiple measurement results, and taking the sum of all the measurement results as the first eigenvalue of each character string; Determine the degree of discreteness of the measured distance between each string and all neighboring strings of each string and the center point of the cluster where the string is located; The level requirement of each character string is composed of the first characteristic value and the discreteness, wherein the level requirement is positively correlated with the first characteristic value and the discreteness respectively; The method of determining the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of each cluster to the character strings in the other clusters contained in the segmentation value of the parent node to which it belongs, includes: Calculate the mean of the measured distances between the string corresponding to each cluster center and the remaining strings in the clusters contained in the parent node segmentation value of each cluster as the first mean; The product of the number of clusters contained in the segmentation value of each cluster parent node and the number of strings in each cluster is used as the first weight; The easy association degree of the access control data information corresponding to each cluster consists of two parts: a first weight and a first mean value, wherein the easy association degree is positively correlated with the first weight, and the easy association degree is negatively correlated with the first mean value.

2. According to claim 1, a data intelligent protection method for preventing loss of access control cards is characterized in that: The determining of the parent node segmentation value of each cluster based on the clustering result includes: In the hierarchical clustering process, when each cluster is treated as a cluster cluster, the upper cluster cluster where the previous split is located is used as the parent node split value of each cluster cluster.

3. According to claim 1, a data intelligent protection method for preventing loss of access control cards is characterized in that: The method for determining the protection level coefficient of each cluster based on the level requirement of the character string and the easy association degree is: Calculate the mean of the rank requirements of all strings in each cluster; The protection level coefficient of each cluster consists of the mean value and the easy association degree of the access control data information corresponding to each cluster. The protection level coefficient is negatively correlated with the mean value and the easy association degree respectively.

4. The method for intelligently protecting data of an access card against loss according to claim 1, characterized in that: The determining of a single secret key string for each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence includes: A hyperchaotic sequence is randomly generated by using a chaotic map, and the hyperchaotic sequence is divided into two initial key streams, wherein the division is divided from any non-endpoint position in the hyperchaotic sequence; The mean value of the protection level coefficients of all clusters is used as the segmentation threshold of the Tent chaotic mapping function to determine the mapping formula; multiple mapping values ​​are iteratively generated using the mapping formula, and a mapping value is randomly assigned to each cluster; The protection level coefficient and mapping value of each cluster are used as a coefficient respectively, and nonlinear transformation is performed on the two initial key streams. The result of the nonlinear transformation is used as a single secret key string of each cluster.

5. The method for intelligently protecting data of an access card against loss according to claim 1, characterized in that: The determining of the label value of a single secret key string based on the protection level coefficient of the cluster where each string is located and the protection level coefficients of the clusters where two adjacent strings of each string are located in the plaintext character sequence includes: Respectively calculating the absolute values ​​of the differences between the protection level coefficient of the cluster where each character string is located and the protection level coefficients of the clusters where the two adjacent characters on the left and right of each character string are located in the plaintext character sequence, and taking the sum of the absolute values ​​of the differences as the first difference; The access control data importance of each string is composed of two parts: the first difference and the protection level coefficient of the cluster where each string is located, wherein the access control data importance is positively correlated with the first difference and the protection level coefficient of the cluster where each string is located; The sum of the access control data importance of all strings in the cluster corresponding to each single secret key string is used as the label value of each single secret key string.

6. The method for intelligently protecting data of an access card against loss according to claim 1, characterized in that: The generating of the round key based on the comparison result of the label value between the single key string and the adjacent right key string includes: The sequence of single secret key strings of all clusters is used as the secret key string sequence of the first round; S1: Determine the comparison result of the label value of each single key string in the first round of key string sequence and the adjacent key string on the right; S2: determining the displacement length of each single secret key string based on the comparison result, and determining the key string of the second round corresponding to each single secret key string in the secret key string sequence of the first round based on the displacement length; S3: traverse a single secret key string in the secret key string sequence of the first round, and use the sequence of key strings obtained as the key string sequence of the second round; S4: Based on the comparison result of the label value of each single key string in the second round of key string sequence with the adjacent key string on the right, repeat steps S2 and S3.

7. The method for intelligently protecting data of an access card against loss according to claim 1, characterized in that: The step of encrypting the plaintext character sequence based on the round key and storing the plaintext group and the ciphertext group compressed from the plaintext group in each sector includes: The plaintext character sequence is used as the input of the block encryption algorithm, the plaintext character sequence is divided into a preset number of plaintext groups, the secret key string sequence of each round is used as the encryption key of each plaintext group, and the ciphertext group of each plaintext group is obtained; Each ciphertext group is compressed, and the compressed ciphertext group and the plaintext group are placed in a sector in the access control card storage space.

8. An intelligent data protection system for preventing access card loss, characterized in that: The system comprises: An acquisition module, used to acquire the data to be protected and determine a plain text character sequence of the data to be protected, wherein the data to be protected is any data that can be read from an access control card in the access control system; A classification module is used to divide the plain text character sequence into strings of 4 bytes in length, and determine the level requirement of each string based on the similarity between each string and all cluster center points contained in the parent node segmentation value of the cluster to which it belongs with its neighboring strings; A calculation module is used to determine the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of each cluster to the character strings in the remaining clusters contained in the parent node segmentation value; and determine the protection level coefficient of each cluster based on the level requirement of the character string and the easy association degree; A determination module, used for determining a single secret key string of each cluster based on the protection level coefficient and the key stream obtained by segmenting the hyperchaotic sequence; A generation module, used to determine the label value of a single secret key string based on the protection level coefficient of the cluster where each string is located and the protection level coefficients of the clusters where two adjacent strings of each string are located in the plaintext character sequence, and generate a round key based on the comparison result of the label value of the single secret key string and the secret key string adjacent to the right; A protection module, used for storing the plaintext group and the ciphertext group compressed from the plaintext group in each sector; The step of determining the level requirement of each string based on the similarity between each string and its neighboring strings among all cluster center points included in the parent node segmentation value of the cluster to which it belongs includes: Taking all the strings as input, using a hierarchical clustering algorithm to obtain clustering results of the strings, and determining the parent node segmentation value of each cluster cluster based on the clustering results; Get the neighboring strings of each string, and take the sequence consisting of the measured distances between each string and all cluster center points contained in the parent node segmentation value of the cluster to which it belongs in ascending order as the distance sequence of each string; Performing similarity measurement on the distance sequence between each character string and any of the neighboring character strings to obtain multiple measurement results, and taking the sum of all the measurement results as the first eigenvalue of each character string; Determine the degree of discreteness of the measured distance between each string and all neighboring strings of each string and the center point of the cluster where the string is located; The level requirement of each character string is composed of the first characteristic value and the discreteness, wherein the level requirement is positively correlated with the first characteristic value and the discreteness respectively; The method of determining the easy association degree of the access control data information corresponding to each cluster based on the attraction degree of each cluster to the character strings in the other clusters contained in the segmentation value of the parent node to which it belongs, includes: Calculate the mean of the measured distances between the string corresponding to each cluster center and the remaining strings in the clusters contained in the parent node segmentation value of each cluster as the first mean; The product of the number of clusters contained in the segmentation value of each cluster parent node and the number of strings in each cluster is used as the first weight; The easy association degree of the access control data information corresponding to each cluster consists of two parts: a first weight and a first mean value, wherein the easy association degree is positively correlated with the first weight, and the easy association degree is negatively correlated with the first mean value.

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