Attribute inference attack defense method and device, electronic equipment, storage medium and computer program product

By eliminating privacy clues through a fine-grained anonymization module and combining iteratively optimized perturbation suffix defense methods, the problem of poor defense against attribute inference attacks in existing technologies is solved, achieving more secure privacy protection.

CN121479835APending Publication Date: 2026-02-06INST OF AUTOMATION CHINESE ACAD OF SCI
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Patent Information

Application Number
CN202511676612.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-14
Publication Date
2026-02-06

AI Technical Summary

Technical Problem

Existing technologies are insufficient to effectively defend against attribute inference attacks, posing a high risk of user privacy leaks. Text-based anonymization methods are coarse-grained, and optimization methods are computationally expensive and difficult to apply to privacy defense.

Method used

A fine-grained anonymization module is used to eliminate privacy clues, and a target perturbation suffix is ​​added through a privacy protection optimization module to prevent attribute inference attack models from obtaining user privacy-related content. The perturbation suffix is ​​optimized iteratively to improve the defense effect.

Benefits of technology

It achieves comprehensive and stable defense against attribute inference attacks, significantly reduces the risk of user privacy leaks, and provides more secure privacy protection.

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Abstract

The invention relates to an attribute inference attack defense method and device, electronic equipment, a storage medium and a computer program product. The method comprises the steps of obtaining a target text; inputting the target text into a fine-grained anonymization module to eliminate privacy clues in the target text so as to obtain an anonymized text; and inputting the anonymized text into a privacy protection optimization module to add a target perturbation suffix for the anonymized text so as to obtain a perturbation text, the target perturbation suffix being used for preventing the attribute inference attack model from obtaining contents related to user privacy in the target text. In this way, by combining two mechanisms of eliminating privacy clues and preventing privacy inference, the advantage of each mechanism can be fully utilized to defend attribute inference attacks. Compared with a single defense means, the defense method provided by the invention can defend the attribute inference attack more comprehensively and more stably, so that the risk of user privacy disclosure can be effectively reduced, and safer and more thorough privacy protection can be provided for the user.
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