Private data protection method capable of automatically adjusting access time
By decomposing the private data space and generating tokens, the problem of individual differential access control in the prior art is solved, the secure access control of private data and the quantitative processing of user access behavior are realized, and the security of database access is improved. sex.
Patent Information
- Application Number
- CN202411323721.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-20
- Publication Date
- 2025-01-10
AI Technical Summary
The prior art cannot realize individual differential access control, resulting in the problem of theft of privacy data.
By obtaining user data, decomposing the privacy data space, generating public keys and private keys, determining the privacy data viewing time based on user reputation value, generating user tokens, and verifying the token in the database, starting a timer to control the privacy data visit time.
It realizes secure access control for private data, improves security when users access databases, and quantifies the user's access behavior.
Smart Images
Figure CN119293839A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of information security technology, and in particular to a privacy data protection method with self-adjustment of access time. Background Art
[0002] A database is a data warehouse that classifies and stores data based on differences in data structure, which can realize the sharing and centralized management of massive data. The database can use a certain method to store data together, which can not only be shared with multiple users, but also separated from the application. In addition, the database can also manage massive data, thereby strictly controlling the number of times the data is accessed and scientifically organizing the data transmission link. Whether it is an organization or an individual, when using the database, some important information will be saved, which means that a large number of users access the database every day. Therefore, data protection in the system has become more and more valued, and people are also constantly studying data privacy protection. How to reasonably access private data in the access control process has been deeply discussed, but the existing technology still has the problem of being unable to achieve individual differential access control and the theft of private data.
[0003] Therefore, it is an urgent problem for those skilled in the art to propose a privacy data protection method with self-adjusting access time to solve the problems existing in the prior art. Summary of the invention
[0004] In view of this, the present invention provides a privacy data protection method with self-adjustment of access time, which helps to quantify the user's access behavior and improve the security of privacy data.
[0005] In order to achieve the above object, the present invention adopts the following technical solution:
[0006] A privacy data protection method with self-adjusting access time includes the following steps:
[0007] S1. Obtain user data and process database data to obtain regular data and privacy data;
[0008] S2, decompose the privacy data space, divide the privacy data into fine-grained, and generate public keys and private keys;
[0009] S3, determining a reputation value based on access user information, and generating a privacy data viewing time based on the user reputation value;
[0010] S4. Generate a user token based on the user data and the public key, and add a private key and a privacy data viewing time to the token based on the user's application;
[0011] S5. The database verifies whether the user token contains the corresponding private key. If so, the timer is started when the user views the space corresponding to the key. When the time recorded by the timer reaches the privacy data viewing time, the token becomes invalid, the privacy space is closed, and the user can continue to query regular data.
[0012] In the above method, optionally, in S2, dividing the privacy data into fine granularity includes: extracting fine-grained features of the privacy data in the database, and then constructing a game equation to divide the privacy data into fine granularity.
[0013] In the above method, optionally, in S2, generating a key includes: encrypting the divided private data, generating and issuing a corresponding key through a secure channel.
[0014] In the above method, optionally, the user reputation value in S3 includes an initial reputation value and a cumulative reputation value.
[0015] In the above method, optionally, the initial reputation value is determined based on the environment information where the user logs in for the first time and the user identity information required to be provided when entering the system;
[0016] The cumulative reputation value is determined based on the associated reputation value and the cumulative reputation value formed by multiple logins of the user.
[0017] In the above method, optionally, the user token in S4 includes a public key, a private key and a reputation value, and the user token accesses regular data by connecting to the database through the public key and decrypts the private data through the private key to access the private data.
[0018] It can be seen from the above technical solution that, compared with the prior art, the present invention provides a privacy data protection method with self-adjustment of access time, which has the following beneficial effects: 1) By encrypting privacy data and establishing a reputation value, a token request mechanism is established to achieve secure access control of privacy data; 2) The present invention quantifies the user's access behavior, improves the security of the user's access to the database, and provides assistance for access control. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] In order to more clearly illustrate the embodiments of the present invention 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 embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.
[0020] Figure 1 The present invention discloses a flow chart of a privacy data protection method with self-adjustment of access time. DETAILED DESCRIPTION
[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0022] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.
[0023] Reference Figure 1 As shown, the present invention discloses a privacy data protection method with self-adjustment of access time, comprising the following steps:
[0024] S1. Obtain user data and process database data to obtain regular data and privacy data;
[0025] S2, decompose the privacy data space, divide the privacy data into fine-grained, and generate public keys and private keys;
[0026] S3, determining a reputation value based on access user information, and generating a privacy data viewing time based on the user reputation value;
[0027] S4. Generate a user token based on the user data and the public key, and add a private key and a privacy data viewing time to the token based on the user's application;
[0028] S5. The database verifies whether the user token contains the corresponding private key. If so, the timer is started when the user views the space corresponding to the key. When the time recorded by the timer reaches the privacy data viewing time, the token becomes invalid, the privacy space is closed, and the user can continue to query regular data.
[0029] Furthermore, in S2, dividing the privacy data into fine granularity includes: extracting fine-grained features of the privacy data in the database, and then constructing a game equation to divide the privacy data into fine granularity.
[0030] Specifically, first, the private data in the database is divided and the private data is initially filtered;
[0031] Then, a data partition equation is constructed based on the filtered privacy data to decompose the privacy data. The privacy decomposition expression is as follows:
[0032] Tal(b t )=f(b t z k ×γ t-1 ),
[0033] Among them, b t represents the probability distribution parameter corresponding to each private data, z k represents the private data partition, γ t-1 Represents the spatial information of private data; then obtains the best response function in the process of fine-grained division of private data to ensure the stability of fine-grained division of private data, and the expression is:
[0034]
[0035] Where W represents the characteristic value of the privacy data, g r represents the allocation function of private data, p r Represents the probability of each data appearing in the corresponding space, ε r represents the fine-grained parameters of different spaces, f rh Represent the probability density function of private data; finally, define the game factor, transform the fine-grained partitioning problem into a planning problem of private data under the least squares criterion, and partition the private data into fine grains.
[0036] Furthermore, in S2, generating a key includes: encrypting the divided private data, generating and issuing a corresponding key through a secure channel.
[0037] Furthermore, the encrypted private data is uploaded to the database to replace the original encrypted data.
[0038] Furthermore, the user reputation value in S3 includes an initial reputation value and a cumulative reputation value.
[0039] Furthermore, the initial reputation value is determined based on the environment information where the user logs in for the first time and the user identity information required to be provided when entering the system;
[0040] The cumulative reputation value is determined based on the associated reputation value and the cumulative reputation value formed by multiple logins of the user.
[0041] Specifically, the environmental information includes IP address, MAC address, access source, etc.
[0042] Furthermore, the initial credibility value is obtained by determining weights for the collected data and assigning values, and the comprehensive data obtained by accumulating the weighted data is used as the initial credibility value.
[0043] The associated reputation value in the cumulative reputation value includes determining different access subjects. Determining the reputation value of subject A includes: determining the evaluation of subject A by other subjects, and sorting the reputation values of the subjects who provide evaluations of subject A in the system, assigning different weights to the corresponding evaluations according to the sorting, and multiplying the evaluation scores by the corresponding weights and then adding them together to obtain the associated reputation value of subject A.
[0044] The accumulated reputation value includes: recording each user's access data to the database as access behavior, determining positive feedback and negative feedback, and increasing the user's reputation value when the access behavior is positive feedback, otherwise it will be reduced. The system administrator can update the access behavior calculation batch by himself. For example, if the reputation value is recalculated after 30 visits, when the user visits more than 30 times, the last visit is set to the 30th, and the access behavior is intercepted forward to recalculate the accumulated reputation value.
[0045] Furthermore, the user token in S4 includes a public key, a private key and a reputation value. The user token connects to the database through the public key to access regular data, and decrypts the private data through the private key to access the private data.
[0046] Furthermore, in S5, some time before the timer in the user token returns to zero, the user can apply for an extension. The system determines whether to extend the time and the extension time based on the user's reputation value. If it is determined that the extension is not possible and the user still needs to view the private data, he / she needs to apply for a token again.
[0047] Specifically, the system administrator can set the time before zeroing, and the total extension time of the user shall not exceed the token recording time.
[0048] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.
[0049] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A privacy data protection method with self-adjusting access time, characterized in that: The following steps are involved: S1. Obtain user data and process database data to obtain regular data and privacy data; S2, decompose the privacy data space, divide the privacy data into fine-grained, and generate public keys and private keys; S3, determining a reputation value based on access user information, and generating a privacy data viewing time based on the user reputation value; S4. Generate a user token based on the user data and the public key, and add a private key and a privacy data viewing time to the token based on the user's application; S5. The database verifies whether the user token contains the corresponding private key. If so, the timer is started when the user views the space corresponding to the key. When the time recorded by the timer reaches the privacy data viewing time, the token becomes invalid, the privacy space is closed, and the user can continue to query regular data.
2. According to claim 1, the privacy data protection method with self-adjustment of access time is characterized in that: In S2, the fine-grained division of privacy data includes: Extract the fine-grained features of the private data in the database, and then construct a game equation to divide the private data into fine-grained levels.
3. According to claim 2, the privacy data protection method with self-adjusting access time is characterized in that: In S2, generating the key includes: Encrypt the divided private data, generate and distribute the corresponding keys through a secure channel.
4. According to claim 1, the privacy data protection method with self-adjusting access time is characterized in that: The user reputation value in S3 includes the initial reputation value and the accumulated reputation value.
5. According to claim 4, the privacy data protection method with self-adjustment of access time is characterized in that: The initial reputation value is determined based on the environment information where the user logs in for the first time and the user identity information required to be provided when entering the system; The cumulative reputation value is determined based on the associated reputation value and the cumulative reputation value formed by multiple logins of the user.
6. The privacy data protection method with self-adjusting access time according to claim 1 is characterized in that: The user token in S4 includes a public key, a private key and a reputation value. The user token connects to the database through the public key to access regular data, and decrypts the private data through the private key to access the private data.