Financial transaction data privacy protection method based on residual sensitivity of differential privacy and related products

By adopting a residual sensitivity method based on differential privacy in the protection of financial transaction data privacy, data noise is calculated and embedded, the problems of high noise levels and large fluctuations in the existing technology are solved, and more effective data privacy protection and data availability are achieved.

CN119691786APending Publication Date: 2025-03-25ZHEJIANG UNIV
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Patent Information

Application Number
CN202411505222.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-24
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

In the prior art, financial transaction data privacy protection methods have problems such as high noise levels and large noise fluctuations, and it is difficult to effectively protect data privacy.

Method used

The residual sensitivity method based on differential privacy is adopted, and the residual sensitivity of the financial transaction data to be shared is calculated by receiving the data sharing request from the demand side, and the data noise is determined based on the preset differential privacy parameters and residual sensitivity, and embedded in the data to be shared to obtain the financial transaction data after privacy protection.

Benefits of technology

It effectively reduces the noise level and noise fluctuations of the financial transaction data obtained by querying, and improves the privacy protection effect and availability of data.

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Abstract

The invention provides a financial transaction data privacy protection method based on residual sensitivity of differential privacy and a related product, and relates to the field of data security, and a specific implementation scheme is as follows: receiving a data sharing request proposed by a demand end, and analyzing to-be-shared financial transaction data required by the demand end from the data sharing request; calculating residual sensitivity corresponding to the financial transaction data to be shared; wherein the residual sensitivity represents a smooth upper bound of the local sensitivity; determining data noise according to a preset differential privacy parameter and residual sensitivity; and embedding the data noise into the financial transaction data to be shared to obtain the financial transaction data after privacy protection processing, and sharing the financial transaction data after privacy protection processing to the demand end. Through the implementation of the financial transaction data privacy protection method, the noise level and noise fluctuation of financial transaction data obtained through query can be effectively reduced.
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