A shared management method for privacy data

Abstract

The present invention discloses a method for sharing and managing private data, including the following steps: S1, determining the privacy protection level of uploaded data according to the privacy preference of the user, and classifying and storing the uploaded data according to the privacy protection level; S2, verifying the reliability of the user uploading data and tracing the data after uploading to obtain the traceability data; S3, making policy judgments through the traceability data updated in real time, completing the data permission access control and user behavior management. In view of the problem of poor sharing security in data transmission, the tracking and management of user privacy data is realized through a specific traceability mechanism. Under the premise of clear data ownership and management rights, the present invention focuses on the confirmation of data use rights and the corresponding data security and privacy protection responsibilities from a technical level, so that the scheme of the present invention can generate higher quality data at the same privacy cost and better complete downstream tasks.

Description

Technical Field

[0001] The present invention belongs to the technical field of data security, and in particular relates to a method for sharing and managing private data. Background Art

[0002] With the rapid development and continuous innovation of computer technology and the Internet of Things, the importance of data has been further reflected, and data has become an important support for building machine learning tasks. For the trusted sharing of data, in order to promote the development of intelligent analysis applications in various scenarios, establishing a data security sharing platform has become a key research trend. Data is transmitted from one organization or system to another for cooperation and analysis. However, the privacy protection that can be achieved by traditional data sharing solutions is limited. In the process of data sharing, most systems have not taken strong data protection measures. There is an inevitable risk of being cracked and leaked during data transmission, resulting in poor data sharing security and making it difficult to ensure data privacy. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, a method for sharing and managing private data provided by the present invention solves the problem of poor sharing security in data transmission.

[0004] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a method for sharing and managing private data, comprising the following steps:

[0005] S1. Determine the privacy protection level of uploaded data based on the privacy preference of the user, and classify and store the uploaded data according to the privacy protection level;

[0006] S2. Verify the reliability of the data uploaded by the user and trace the data after uploading to obtain the traceability data;

[0007] S3. Make policy decisions through real-time updated traceability data to complete data access control and user behavior management.

[0008] Further: In S1, the method for determining the privacy protection level of uploaded data by the user according to the privacy preference is specifically:

[0009] The gradient is perturbed in the uploaded data to determine the different levels of privacy protection for the uploaded data. The specific expression is:

[0010]

[0011] In the formula, For machine learning models, is the minimum batch data, is the stochastic gradient, is Gaussian noise.

[0012] The beneficial effect of the above further solution is that when users upload data, the gradient will be perturbed to achieve differential privacy and resist attacks from the server.

[0013] Further: In S1, the method for classifying and storing uploaded data according to the privacy protection level is specifically as follows:

[0014] According to the data classification model, the uploaded data is divided into nest data and guardian data, the mapping relationship between nest data and guardian data is defined, and the nest data and guardian data are updated synchronously. Among them, the nest data includes the user's private data and uploaded data. The user's private data is generated after encryption based on the uploaded data. The guardian data point includes the sensitive fields of the private data and the encryption method corresponding to each sensitive field.

[0015] The beneficial effect of the above further scheme is: the uploaded data is divided into nest and guardian, and then further classified and marked according to the privacy protection level, importance and sensitivity of the data, which greatly improves the privacy security of the data.

[0016] Further: in said S2, the traceability data includes the traceability created by the nest data and the traceability created by the guardian data;

[0017] The traceability created by nest data includes the first data point ID, the previous state traceability address and the first traceability. The first traceability includes the uploader of the data point, the time tag, the user's private data and the uploaded data.

[0018] The traceability created by guardian data includes the second data point ID, the derived data point traceability set and the second traceability. The second traceability is used to store sensitive fields of privacy data and the encryption method corresponding to each sensitive field.

[0019] The beneficial effects of the above further scheme are: nest data records detailed information of each data uploaded by the user for easy tracking and management. Starting from the traceability, the present invention proposes a strategy that maps each data point to a set of related and independent traceability, which is flexible and scalable.

[0020] Further: The method of creating and tracing the source of nest data is as follows:

[0021] In response to user uploading data, nest data is created;

[0022] In response to changes in the user's uploaded data, the corresponding nest data point is updated to record the latest changed data;

[0023] During the period when users upload data, new traceability records are generated based on important events set by users to record all the user's changed data.

[0024] Further: The specific method of creating traceability for guardian data points is:

[0025] Monitor and record real-time data during user data upload and create guardian data points;

[0026] Update the guardian data point according to the real-time status and security information of the privacy data during the user uploading data;

[0027] Generate a traceability record for each guardian data point to record all real-time data and trace it back to a specific point in time.

[0028] Further: The method of synchronously updating nest data and guardian data is as follows:

[0029] In response to the system uploading nest data, multiple guardian data points are selected to record the real-time data uploaded by the user;

[0030] Create a traceability record for the nest data and related guardian data. The traceability record is mapped to the nest data ID through a unique traceability ID to ensure that the encryption method of the encrypted privacy data corresponding to the uploaded data is the same as the agreed encryption method, ensuring the encryption security of each data point.

[0031] The beneficial effects of the above further scheme are: synchronously updating nest data and guardian data, ensuring the security and accuracy of data in an environment with many sources and high data redundancy, and achieving the purpose of enhancement and protection.

[0032] Further: S3 is specifically:

[0033] The user's operation application is subject to policy judgment based on the current traceability. The operation is executed after the judgment is passed. After the operation is executed, new traceability data is generated and uploaded to the chain. The newly generated traceability data serves as the basis for the next policy judgment.

[0034] The beneficial effects of the present invention are:

[0035] (1) The present invention provides a method for sharing and managing private data. To address the problem of poor sharing security in data transmission, the present invention implements tracking and management of private data in user uploaded data through a specific traceability mechanism. On the premise that data ownership and management rights are clear, the present invention focuses on the confirmation of data usage rights and the confirmation of corresponding data security and privacy protection responsibilities from a technical perspective, so that the scheme of the present invention can generate higher quality data at the same privacy cost, better complete downstream tasks, and ensure that the identity privacy of participating users is not disclosed during the data interaction process.

[0036] (2) The privacy protection level method proposed in this invention takes into account that users have different privacy preferences and meets their personalized privacy protection needs. It can better balance the relationship between data quality and privacy protection and can adapt to the consensus mechanism of multi-user interaction. It is expected that in high user concurrency scenarios, the system throughput can be increased to 1.5 times the original, effectively meeting the data interaction and management needs in large-scale user scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 The present invention is a flow chart of a method for sharing and managing privacy data. DETAILED DESCRIPTION

[0038] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0039] like Figure 1 As shown, in one embodiment of the present invention, a method for sharing and managing private data includes the following steps:

[0040] S1. Determine the privacy protection level of uploaded data based on the privacy preference of the user, and classify and store the uploaded data according to the privacy protection level;

[0041] S2. Verify the reliability of the data uploaded by the user and trace the data after uploading to obtain the traceability data;

[0042] S3. Make policy decisions through real-time updated traceability data to complete data access control and user behavior management.

[0043] In S1, the method for determining the privacy protection level of uploaded data by the user according to the privacy preference is specifically as follows:

[0044] The gradient is perturbed in the uploaded data to determine the different levels of privacy protection for the uploaded data. The specific expression is:

[0045]

[0046] In the formula, For machine learning models, is the minimum batch data, is the stochastic gradient, is Gaussian noise.

[0047] In this embodiment, the gradient is perturbed when the user uploads data to achieve differential privacy and resist attacks from the server.

[0048] In S1, the method for classifying and storing uploaded data according to the privacy protection level is specifically as follows:

[0049] According to the data classification model, the uploaded data is divided into nest data and guardian data, the mapping relationship between nest data and guardian data is defined, and the nest data and guardian data are updated synchronously. Among them, the nest data includes the user's private data and uploaded data. The user's private data is generated after encryption based on the uploaded data. The guardian data point includes the sensitive fields of the private data and the encryption method corresponding to each sensitive field.

[0050] In this embodiment, the uploaded data is divided into nest and guardian, and then further classified and marked according to the privacy protection level, importance and sensitivity of the data, which greatly improves the privacy security of the data.

[0051] In S2, the traceability data includes the traceability created by the nest data and the traceability created by the guardian data;

[0052] The traceability created by nest data includes the first data point ID, the previous state traceability address and the first traceability. The first traceability includes the uploader of the data point, the time tag, the user's private data and the uploaded data.

[0053] The traceability created by guardian data includes the second data point ID, the derived data point traceability set and the second traceability. The second traceability is used to store sensitive fields of privacy data and the encryption method corresponding to each sensitive field.

[0054] In this embodiment, nest data records detailed information of each data upload by the user for easy tracking and management. Starting from the traceability, the present invention proposes a strategy that maps each data point to a set of related and independent traceability. This strategy is flexible and scalable.

[0055] The data classification model includes agents, processes and artifacts, where agents correspond to system users, processes are used to capture functional behaviors, including upload, access and update, and artifacts are used to record data objects. The dependencies between components in the causal dependency traceability model include process to artifact, artifact to process and process to agent.

[0056] Among them, in the dependency relationship between the process and the artifact, the attributes include writable and read-only, and the process instances include Upload, Update and Visit, where the instances Update and Visit are used to indicate the protection identifier of the data whose status has changed;

[0057] The nodes of DAG are components in the traceability model of causal dependency, and the edges of DAG are dependencies between components in the traceability model of causal dependency.

[0058] The specific method of creating and tracing the source of nest data is as follows:

[0059] In response to user uploading data, nest data is created;

[0060] In response to changes in the user's uploaded data, the corresponding nest data point is updated to record the latest changed data;

[0061] During the period when users upload data, new traceability records are generated based on important events set by users to record all the user's changed data.

[0062] The specific method for creating a traceability for a guardian data point is:

[0063] Monitor and record real-time data during user data upload and create guardian data points;

[0064] Update the guardian data point according to the real-time status and security information of the privacy data during the user uploading data;

[0065] Generate a traceability record for each guardian data point to record all real-time data and trace it back to a specific point in time.

[0066] The specific method for synchronously updating nest data and guardian data is:

[0067] In response to the system uploading nest data, multiple guardian data points are selected to record the real-time data uploaded by the user;

[0068] Create a traceability record for the nest data and related guardian data. The traceability record is mapped to the nest data ID through a unique traceability ID to ensure that the encryption method of the encrypted privacy data corresponding to the uploaded data is the same as the agreed encryption method, ensuring the encryption security of each data point.

[0069] In this embodiment, the nest data and guardian data are updated synchronously, which ensures the security and accuracy of data in an environment with multiple sources and high data redundancy, thereby achieving the purpose of enhancement and protection.

[0070] The S3 is specifically:

[0071] The user's operation application is subject to policy judgment based on the current traceability. The operation is executed after the judgment is passed. After the operation is executed, new traceability data is generated and uploaded to the chain. The newly generated traceability data serves as the basis for the next policy judgment.

[0072] In this embodiment, uploading regulatory data to the chain and tracing the data are important means to ensure the credibility of the system. In view of the possible malicious attacks and leakage of user privacy data during the data upload process, which poses a great threat to the security of the entire system, the present invention performs strategy judgment through the current traceability during the data upload stage, effectively ensures the integrity of on-chain data transmission, realizes dynamic access control, and ensures the security of privacy data.

[0073] The beneficial effects of the present invention are as follows: the present invention provides a method for sharing and managing privacy data. In view of the problem of poor sharing security in data transmission, the present invention realizes the tracking and management of privacy data in user uploaded data through a specific traceability mechanism. On the premise that data ownership and management rights are clear, the present invention focuses on the confirmation of data usage rights and the corresponding data security and privacy protection responsibilities from a technical level, so that the scheme of the present invention can generate higher quality data at the same privacy cost, better complete downstream tasks, and ensure that the identity privacy of participating users is not disclosed during the data interaction process.

[0074] The privacy protection level method proposed in the present invention takes into account that users have different privacy preferences and meets their personalized privacy protection needs. It can better balance the relationship between data quality and privacy protection, and can adapt to the consensus mechanism of multi-user interaction. It is expected that in high user concurrency scenarios, the system throughput can be increased to 1.5 times the original, effectively meeting the data interaction and management needs in large-scale user scenarios.

[0075] In the description of the present invention, it is necessary to understand that the orientation or positional relationship indicated by the terms "center", "thickness", "upper", "lower", "horizontal", "top", "bottom", "inner", "outer", "radial", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", and "third" are used only for descriptive purposes, and cannot be understood as indicating or implying the relative importance or the number of implicitly specified technical features. Therefore, the features defined by "first", "second", and "third" may explicitly or implicitly include one or more of the features.

Claims

1. A method for sharing and managing private data, characterized in that: The following steps are involved: S1. Determine the privacy protection level of uploaded data based on the privacy preference of the user, and classify and store the uploaded data according to the privacy protection level; S2. Verify the reliability of the data uploaded by the user and trace the data after uploading to obtain the traceability data; S3: Make policy decisions through real-time updated traceability data to complete data access control and user behavior management; In S1, the method for determining the privacy protection level of uploaded data by the user according to the privacy preference is specifically as follows: The gradient is perturbed in the uploaded data to determine the different levels of privacy protection for the uploaded data. The specific expression is: In the formula, For machine learning models, is the minimum batch data, is the stochastic gradient, is Gaussian noise; In S1, the method for classifying and storing uploaded data according to the privacy protection level is specifically as follows: According to the data classification model, the uploaded data is divided into nest data and guardian data, the mapping relationship between nest data and guardian data is defined, and the nest data and guardian data are updated synchronously. The nest data includes the user's private data and uploaded data. The user's private data is generated after encryption based on the uploaded data. The guardian data point includes the sensitive fields of the private data and the encryption method corresponding to each sensitive field. In S2, the traceability data includes the traceability created by the nest data and the traceability created by the guardian data; The traceability created by nest data includes the first data point ID, the previous state traceability address and the first traceability. The first traceability includes the uploader of the data point, the time tag, the user's private data and the uploaded data. The traceability created by guardian data includes the second data point ID, the derived data point traceability set and the second traceability. The second traceability is used to store sensitive fields of private data and the encryption method corresponding to each sensitive field; The specific method for synchronously updating nest data and guardian data is: In response to the system uploading nest data, multiple guardian data points are selected to record the real-time data uploaded by the user; Create a traceability record for the nest data and related guardian data. The traceability record is mapped to the nest data ID through a unique traceability ID to ensure that the encryption method of the encrypted private data corresponding to the uploaded data is the same as the agreed encryption method, ensuring the encryption security of each data point; The S3 is specifically: The user's operation application is subject to policy judgment based on the current traceability. The operation is executed after the judgment is passed. After the operation is executed, new traceability data is generated and uploaded to the chain. The newly generated traceability data serves as the basis for the next policy judgment.

2. The method for sharing and managing private data according to claim 1, characterized in that: The specific method of creating and tracing the source of nest data is as follows: In response to user uploading data, nest data is created; In response to changes in the user's uploaded data, the corresponding nest data point is updated to record the latest changed data; During the period when users upload data, new traceability records are generated based on important events set by users to record all the user's changed data.

3. The method for sharing and managing private data according to claim 2, characterized in that: The specific method for creating a traceability for a guardian data point is: Monitor and record real-time data during user data upload and create guardian data points; Update the guardian data point according to the real-time status and security information of the privacy data during the user uploading data; Generate a traceability record for each guardian data point to record all real-time data and trace it back to a specific point in time.

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