Real estate mortgage registration system integrated with information security sharing function

Abstract

The invention relates to the technical field of data security, in particular to a real estate mortgage registration system integrated with an information security sharing function. The system comprises an information acquisition module used for acquiring registration data of real estate mortgage; the data storage module is used for carrying out distributed storage on the registration data; the data sharing module is used for sharing the to-be-shared registration data to a receiver, and specifically comprises the following steps: acquiring each batch of to-be-shared registration data; acquiring a data difference degree of single registration data; obtaining a discrete adjustment value of single registration data; obtaining the privacy budget correction degree of the single registration data so as to correct the initial preset privacy budget of the single registration data; and performing differential privacy noise addition on all the to-be-shared registration data, and transmitting the to-be-shared registration data after noise addition to a receiver. According to the method and the device, the privacy budget when differential privacy noise addition is performed on each registration data is adaptively calculated, so that the availability and the security after information sharing are improved.

Description

Technical Field

[0001] This application relates to the field of data security technology, and particularly relates to a real estate mortgage registration system integrating information security sharing functions. Background Art

[0002] In recent years, some regions have achieved limited sharing of real estate registration information by establishing collaborative platforms. However, since there is a large amount of private data in real estate mortgage registration information data and it is extremely vulnerable to differential attacks and then disclose a large amount of private data, therefore, there is an urgent need for a real estate mortgage registration system integrating information security sharing functions, which is of great significance for improving business efficiency and security.

[0003] Currently, how to improve the security of real estate mortgage registration data when it is under differential attack has become a research hotspot. The patent "CN116484400A Data Sharing System and Method Based on Notary Mechanism and Differential Privacy Algorithm" mentions using the differential privacy algorithm to perform differential privacy calculation processing on private data and form noisy private data. However, there are still some deficiencies in the above-mentioned solution. When adding noise using the differential privacy algorithm, usually the same privacy budget value is used for different data, without considering the degree of difference in registration data and whether the similarity degree of the inherent content in the registration data matches the privacy budget. When the set privacy budget is too small, too much noise is added to the original data, resulting in low data availability; when the set privacy budget is too large, the protection intensity for the data is weak, and the security is low when under differential attack. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a real estate mortgage registration system integrating information security sharing functions, and the specific technical solutions adopted are as follows:

[0005] This application proposes a real estate mortgage registration system integrating information security sharing functions, and the system includes:

[0006] An information acquisition module, used to acquire registration data of real estate mortgages;

[0007] A data storage module, used to perform distributed storage on the registration data;

[0008] A data sharing module, used to share the registration data to be shared with the receiving party, specifically:

[0009] S1: Acquire each batch of registration data to be shared;

[0010] S2: Obtain the data difference degree of a single registration data according to the edit distance between the single registration data and other registration data in the same batch, and the difference in the total number of data categories; cluster all the registration data in the same batch, and obtain the average cluster interval of the single-batch registration data according to the edit distance between the registration data corresponding to every two cluster centers; and combine the total number of clusters in the batch where the single registration data is located to obtain the discrete adjustment value of the single registration data; obtain the privacy budget correction degree of the single registration data according to the data difference degree and the discrete adjustment value of the single registration data, so as to correct the initial preset privacy budget of the single registration data;

[0011] S3: Add differential privacy noise to all the registration data to be shared, and transmit the noisy registration data to be shared to the recipient.

[0012] Preferably, the process of obtaining the edit distance between the single registration data and other registration data in the same batch is as follows: construct all the contents in each registration data into a string respectively, and use the edit distance between the string corresponding to the single registration data and the strings corresponding to other registration data in the same batch as the edit distance between the single registration data and other registration data in the same batch.

[0013] Preferably, the calculation formula of the data difference degree of the single registration data is: ; where is the data difference degree of the i-th registration data, is the average edit distance between the i-th registration data and other registration data in the same batch, is the average value of the difference in the total number of data categories within the i-th registration data and other registration data in the same batch.

[0014] Preferably, the specific process of clustering all the registration data in the same batch is as follows: take all the registration data in the same batch as the input of the DPC density peak clustering algorithm, use the edit distance between every two registration data as the metric distance, and divide all the registration data in the same batch into multiple clusters.

[0015] Preferably, the process of obtaining the average cluster interval of the single-batch registration data is as follows: after clustering the single-batch registration data, use the edit distance between the registration data corresponding to any two cluster centers as the interval value between the two clusters, and use the average value of the interval values between all the clusters of the single-batch registration data as the average cluster interval of this batch of registration data.

[0016] Preferably, the calculation formula of the discrete adjustment value of the single registration data is: ; where is the discrete adjustment value of the i-th registration data, is the total number of clustering clusters after clustering all the registration data to be shared in the batch where the i-th registration data is located, is the average value of the clustering cluster intervals of the registration data to be shared in the batch where the i-th registration data is located, is a preset constant.

[0017] Preferably, the privacy budget correction degree of the single registration data is the sum or product of the data difference degree and the discrete adjustment value of the single registration data.

[0018] Preferably, the privacy budget after correcting the initial preset privacy budget of the single registration data is: ; in the formula, is the privacy budget after correction of the i-th registration data, is the initial preset privacy budget of the differential privacy algorithm, is the privacy budget correction degree of the i-th registration data.

[0019] Preferably, the specific process of adding differential privacy noise to all the registration data to be shared is as follows: after the data sharing module obtains a batch of registration data to be shared, it calculates the privacy budget after correction of each registration data, and adds noise to the corresponding registration data according to the privacy budget by using the differential privacy algorithm.

[0020] Preferably, after transmitting the noisy registration data to be shared to the receiving party, the receiving party stores it by using the data storage module.

[0021] The present application has the following beneficial effects:

[0022] By analyzing the difference situation between the registration data to be shared in the real estate mortgage registration system and the similarity situation of the inherent content, the present application obtains the privacy budget correction degree of each registration data, and then adaptively corrects the privacy budget of each registration data. Furthermore, according to the privacy budget after correction of each registration data, the differential privacy algorithm is used to add noise to each registration data, so as to ensure the availability of the data after sharing while ensuring the security of the data. This solves the problem of low data availability and security caused by using the same privacy budget value for the real estate mortgage registration data by the current differential privacy algorithm without considering the difference degree of the registration data and the matching degree between the similarity degree of the inherent content in the registration data and the privacy budget, and improves the availability and security of the data after sharing. Description of the Drawings

[0023] To more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0024] Figure 1 Block diagram of a real estate mortgage registration system integrating information security sharing function provided by an embodiment of the present application;

[0025] Figure 2 Flowchart for correcting the initial preset privacy budget for each registration data provided by an embodiment of the present application. Detailed implementation manners

[0026] To further elaborate on the technical means and effects adopted by the present application to achieve the intended invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of a real estate mortgage registration system integrating information security sharing function proposed according to the present application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0028] The following specifically describes the specific solution of a real estate mortgage registration system integrating information security sharing function provided by the present application in combination with the accompanying drawings.

[0029] Please refer to Figure 1 , which shows a block diagram of a real estate mortgage registration system integrating information security sharing function provided by an embodiment of the present application. The system includes: an information acquisition module, a data storage module, and a data sharing module.

[0030] Information acquisition module: used to acquire the registration information of real estate mortgages. This module also integrates a submitter identity information verification module. After a person performs a submission operation at the front end, a preliminary identity verification will be carried out. The system verifies the identity information of the person by sending a one-time password request for verification, classifies the acquired registration data according to established rules, organizes files in different formats into the same format, and backs up the original data at the same time.

[0031] Data storage module: It is used to perform distributed storage on the registered data after preprocessing and the original backup data, which facilitates the management and search of a large amount of data. When modifying or deleting the stored data, the identity verification and confirmation of the management personnel are required.

[0032] Data sharing module: It is used to share the registered data to be shared with the recipient. This module integrates:

[0033] Network data transmission function: It is used to establish connections with other regions and the central server to form a connection network.

[0034] Authentication and authorization verification function: It is used for identity verification and permission verification of shared requests from real estate mortgage registration systems in different regions.

[0035] Information security sharing function: It is used to protect the process of sharing registered data. The implementation process of this function includes the following steps:

[0036] S1: Obtain each batch of registered data to be shared.

[0037] The data storage module of the real estate mortgage registration system transfers the data to be shared in batches to the sharing module of the real estate mortgage registration system. In this embodiment, the registered data to be shared in the same batch is taken as an example for processing. Among them, the registered data to be shared in the same batch contains multiple registered data.

[0038] S2: Obtain the data difference degree of a single registered data according to the edit distance between the single registered data and other registered data in the same batch, and the difference in the total number of data categories; cluster all the registered data in the same batch, and obtain the average cluster interval of the single batch of registered data according to the edit distance between the registered data corresponding to the centers of each two clusters; and combine the total number of clusters in the batch where the single registered data is located to obtain the discrete adjustment value of the single registered data; obtain the privacy budget correction degree of the single registered data according to the data difference degree and the discrete adjustment value of the single registered data, so as to correct the initial preset privacy budget of the single registered data.

[0039] Differential Privacy is a privacy protection technology aimed at protecting individual privacy during the data release or analysis process. Its core idea is to add noise to the data so that attackers cannot accurately judge whether an individual participated in the data set from the analysis results, thereby protecting individual privacy. In the differential privacy algorithm, the privacy budget is used to control the privacy protection level of the algorithm. The smaller the privacy budget, the more noise is added, and the stronger the protection effect of the algorithm; the larger the privacy budget, the less noise is added, and the weaker the protection effect of the algorithm.

[0040] Under normal circumstances, a single registration data contains a relatively large number of data categories, including but not limited to mortgagees, registration numbers, document types, document numbers, house addresses, etc. There are significant differences among the same batch of registration data to be shared, and it is difficult for attackers to obtain the remaining information based on partial information. However, when a single user submits multiple registration data or duplicate data at one time, there are some data that are the same in the same registration data or there are only partial data category differences between the data. When attackers perform differential attacks on such data, because there are more identical data, it is easier to compare the remaining information data and easier to steal information. Therefore, for such data, the privacy budget should be reduced to ensure security during the sharing process. In addition, since each registration data contains a relatively large number of data categories, and the number of data categories required for registration may vary due to different types of actual real estate, among the data obtained by the real estate mortgage registration information acquisition module, there may be a situation where the total number of data categories in some registration data is different from the total number of data categories in the remaining registration data. The greater the difference in the data categories contained in each registration data, the more difficult it is for attackers to obtain the remaining information through partial information. Therefore, a relatively large privacy budget can be set for this part of the data.

[0041] According to the above analysis, for a single registration data, when adding noise using the differential privacy algorithm, the privacy budget can be adjusted to a certain extent according to the difference between the registration data and other registration data. As a preferred implementation, based on the edit distance between a single registration data and other registration data in the same batch, as well as the difference in the total number of data categories, a data difference degree of the single registration data is constructed to represent the difference between the single registration data and other registration data in the same batch.

[0042] In this embodiment, the data difference degree of the i-th registration data to be shared is denoted as , and its specific expression is: ; in the formula, is the data difference degree of the i-th registration data, is the average value of the edit distances between the i-th registration data and other registration data in the same batch, is the average value of the difference in the total number of data categories between the i-th registration data and other registration data in the same batch. The calculation of the edit distance between two data is a well-known technology, and the specific process will not be elaborated here.

[0043] It should be noted that the specific process of calculating the edit distance between two registration data is as follows: all the contents in the two registration data are respectively constructed into a string, and the edit distance between the strings corresponding to the two registration data is used as the edit distance between the two registration data.

[0044] When the similarity between a single registered data and other registered data in the same batch of registered data to be shared is smaller and the difference in the total number of data categories is larger, that is, when the data difference degree of the single registered data is larger, it indicates that the data difference between this registered data and other registered data is larger, and the possibility of obtaining the remaining privacy information when being subjected to a differential attack is smaller. Therefore, the privacy budget adopted for this data can be increased.

[0045] Furthermore, due to the local nature of the real estate mortgage registration system, that is, among the registered data within the same city, the locations of houses are relatively close, that is, the similarity degree of data in the real estate address is higher. In addition, for the registered data, in addition to the data that can be filled in, there is also a part of the content that is the inherent content in the registration form, such as filling instructions, remarks, option descriptions, etc. Therefore, only adjusting the privacy budget through the above method may reduce the privacy budget of most data, not only causing the usability of the data to decline, but also wasting more computing resources. Therefore, when the similarity of some inherent content in the same batch of registered data is relatively high, there is no need to reduce the privacy budget.

[0046] Due to the local characteristics of the above-mentioned registered data, there is a small amount of similarity in the data category content between each registered data, but the content in the remaining data categories is quite different. Therefore, the distribution of the registered data as a whole is relatively discrete, but the difference degree between each data is similar. Taking all the registered data in the same batch as the input of the DPC density peak clustering algorithm, using the edit distance between every two registered data as the metric distance, and setting the truncation distance to 5 in this embodiment, all the registered data in the same batch are divided into multiple clustering clusters. Among them, the DPC density peak clustering algorithm is a well-known technology, and the specific process will not be elaborated here.

[0047] As a preferred implementation manner, the clustering cluster interval mean of a single batch of registered data is obtained according to the edit distance between the registered data corresponding to the centers of every two clustering clusters; and in combination with the total number of clustering clusters in the batch where the single registered data is located, the discrete adjustment value of the single registered data is obtained, which is used to characterize the similarity of the inherent content in each registered data.

[0048] In this embodiment, the discrete adjustment value of the i-th registered data is denoted as , and its specific expression is: ; in the formula, is the discrete adjustment value of the i-th registered data, is the total number of clustering clusters after clustering all the registered data to be shared in the batch where the i-th registered data is located, is the clustering cluster interval mean of the registered data to be shared in the batch where the i-th registered data is located, is a preset constant to prevent the denominator from being zero, and in this embodiment The calculation method of the mean of the cluster intervals is as follows: After clustering the same batch of registration data, the edit distance between the registration data corresponding to any two cluster centers is used as the interval value between the two clusters, and the mean of the interval values between all clusters of the same batch of registration data is used as the mean of the cluster intervals of this batch of registration data.

[0049] Among the data to be shared, the more clusters there are after data clustering, and the smaller the difference in the edit distance between each cluster, it indicates that although there are some approximate data in the registration data, there are still certain differences between the data. The less data can be obtained through differential attacks, so the privacy budget can be increased.

[0050] As a preferred implementation, according to the sum or product of the data difference degree and the discrete adjustment value of each registration data, the privacy budget correction degree of each registration data is constructed.

[0051] In this embodiment, the privacy budget correction degree of the i-th registration data is denoted as , and its specific expression is: ; In the formula, is the privacy budget correction degree of the i-th registration data, is the data difference degree of the i-th registration data, is the discrete adjustment value of the i-th registration data.

[0052] In another embodiment, the expression of the privacy budget correction degree of the i-th registration data can be: ; In the formula, is the privacy budget correction degree of the i-th registration data, is the data difference degree of the i-th registration data, is the discrete adjustment value of the i-th registration data.

[0053] When the difference degree between the i-th registration data and the remaining registration data to be shared is greater, and the data distribution in the registration data to be shared where it is located is more discrete, and the difference situation between the data is more balanced, it indicates that the possibility of information being stolen when this data is subjected to differential attacks is smaller. Therefore, the privacy budget for this data can be increased.

[0054] Furthermore, according to the privacy budget correction degree of each registration data, calculate the corrected privacy budget of each registration data in the differential privacy algorithm: ; In the formula, is the corrected privacy budget of the i-th registration data, is the initial preset privacy budget of the differential privacy algorithm, which is taken as 5 in this embodiment, is the privacy budget correction degree for the i-th registration data. The flowchart for correcting the initial preset privacy budget for each registration data is as follows Figure 2 shown.

[0055] S3: Perform differential privacy noise addition on all registration data to be shared, and transmit the noisy registration data to be shared to the receiving party.

[0056] Whenever the real estate mortgage registration system performs data sharing, after obtaining the registration data to be shared, calculate the corrected privacy budget for each registration data, and use the differential privacy algorithm to add noise to the corresponding registration data according to the privacy budget.

[0057] Furthermore, the network data transmission function of the data sharing module transmits the noisy registration data to be shared to the designated receiving party (the real estate mortgage registration system or the central server in another region) through the communication channel. After the receiving party receives the data, the data is stored in combination with the data storage module, and finally the real estate mortgage registration data is shared from the current local real estate mortgage registration system to the designated local real estate mortgage registration system or the central server.

[0058] So far, a real estate mortgage registration system integrating information security sharing function is completed.

[0059] It should be noted that: the above sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0060] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments.

[0061] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. An immovable property mortgage registration system integrating information security sharing function, characterized in that, The system includes: An information acquisition module, configured to acquire registration data of real estate mortgage; A data storage module, configured to perform distributed storage on the registration data; A data sharing module, configured to share the registration data to be shared with a receiving party. Specifically: S1: Acquire each batch of registration data to be shared; S2: Obtain the data difference degree of a single registration data according to the edit distance between the single registration data and other registration data in the same batch, and the difference in the total number of data categories; cluster all the registration data in the same batch, and obtain the cluster interval mean value of the single batch of registration data according to the edit distance between the registration data corresponding to each two cluster centers; and combine the total number of cluster clusters in the batch where the single registration data is located to obtain the discrete adjustment value of the single registration data; obtain the privacy budget correction degree of the single registration data according to the data difference degree and the discrete adjustment value of the single registration data, so as to correct the initial preset privacy budget of the single registration data; S3: Perform differential privacy noise addition on all the registration data to be shared, and transmit the noise-added registration data to be shared to the receiving party.

2. The real estate mortgage registration system integrating an information security sharing function according to claim 1, characterized in that, The process of obtaining the edit distance between the single registration data and other registration data in the same batch is as follows: construct all the contents in each registration data into a string respectively, and use the edit distance between the string corresponding to the single registration data and the strings corresponding to other registration data in the same batch as the edit distance between the single registration data and other registration data in the same batch.

3. An immovable property mortgage registration system integrating an information security sharing function as claimed in claim 1, characterized in that, The calculation formula for the data difference degree of the single registration data is as follows: ; where is the data difference degree of the i-th registration data, is the average edit distance between the i-th registration data and other registration data in the same batch, is the average value of the difference in the total number of data categories between the i-th registration data and other registration data in the same batch.

4. The real estate mortgage registration system integrating an information security sharing function according to claim 1, characterized in that, The specific process of clustering all the registration data in the same batch is as follows: use all the registration data in the same batch as the input of the DPC density peak clustering algorithm, use the edit distance between each two registration data as the metric distance, and divide all the registration data in the same batch into multiple cluster clusters.

5. An immovable property mortgage registration system integrating an information security sharing function as claimed in claim 1, characterized in that, The process of obtaining the cluster interval mean value of the single batch of registration data is as follows: after clustering the single batch of registration data, use the edit distance between the registration data corresponding to any two cluster centers as the interval value between the two cluster clusters, and use the mean value of the interval values between all the cluster clusters of the single batch of registration data as the cluster interval mean value of this batch of registration data.

6. The real estate mortgage registration system integrating an information security sharing function according to claim 1, characterized in that, The calculation formula for the discrete adjustment value of the single registration data is as follows: ; where is the discrete adjustment value of the i-th registration data, is the total number of clustering clusters after clustering all the registration data to be shared in the batch where the i-th registration data is located, is the mean value of the clustering cluster intervals of the registration data to be shared in the batch where the i-th registration data is located, is a preset constant.

7. An immovable property mortgage registration system integrating an information security sharing function as claimed in claim 1, characterized in that, The privacy budget correction degree of the single registration data is the sum or product of the data difference degree and the discrete adjustment value of the single registration data.

8. An immovable property mortgage registration system integrating an information security sharing function as claimed in claim 1, characterized in that, The privacy budget after correcting the initial preset privacy budget for a single registration data is as follows: ; where is the privacy budget after correcting the i-th registration data, is the initial preset privacy budget of the differential privacy algorithm, is the privacy budget correction degree of the i-th registration data.

9. The real estate mortgage registration system integrating an information security sharing function according to claim 1, characterized in that The specific process of performing differential privacy noise addition on all the registration data to be shared is as follows: after the data sharing module obtains a batch of registration data to be shared, calculate the corrected privacy budget of each registration data, and perform noise addition on the corresponding registration data according to the privacy budget using the differential privacy algorithm.

10. An immovable property mortgage registration system integrating an information security sharing function as claimed in claim 1, characterized in that, After transmitting the noise-added registration data to be shared to the receiving party, the receiving party uses the data storage module for storage.

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