Multi-source data desensitization convergence system based on generative adversarial model

CN119622804APending Publication Date: 2025-03-14THE FIRST RES INST OF MIN OF PUBLIC SECURITY
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Patent Information

Application Number
CN202411689619.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-25
Publication Date
2025-03-14

AI Technical Summary

Technical Problem

Currently, data acquisition faces multiple restrictions, including the need for desensitization of data sensitivity, diverse data sources and large number, making it difficult for enterprises to obtain the required data under generalized data sources. At the same time, in the face of tight network security, how to improve data transmission security and avoid data leakage is also a major challenge.

Method used

A multi-source data desensitization aggregation system based on a generative adversarial model is adopted, including a multi-source desensitization data aggregation module and a cross-domain desensitization data fusion module. The system realizes data anonymization, concealment and security through generalization of IP proxy module, access policy simulation module based on generative adversarial model, desensitization module and flood-based backhaul link generalization module.

Benefits of technology

It significantly improves the concealment and security of the data acquisition process, protects the security and stability of data aggregation behavior, improves the generalization of the aggregation target, realizes the security and rapid back-passing of data, and significantly improves the legality, compliance and efficiency of the data fusion process.

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Abstract

The invention discloses a multi-source data desensitization convergence system based on a generative adversarial model. The multi-source data desensitization convergence system comprises a multi-source desensitization data convergence module and a cross-domain desensitization data fusion module, the multi-source desensitization data aggregation module comprises a generalization IP agent module, an access strategy simulation module based on a generative adversarial model, a desensitization module and a backhaul link generalization module based on flooding; the cross-domain desensitization data fusion module comprises a data security convergence platform, an own data module, an offline data module, an online data module, a multi-party security data module, a big data base module, a cloud data module, a total data module, an open source and semi-open source data module and an internet risk assessment module. According to the method, the open source data of the target network can be widely acquired, the concealment of the data acquisition process is improved, the optimization level of data security and privacy protection can be remarkably improved, the high security of the data in the fusion process is ensured, and the leakage of sensitive information is effectively prevented.
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Citation Information

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