数据与计算发展前沿2025，Vol.7Issue(3)：48-66,19.DOI:10.11871/jfdc.issn.2096-742X.2025.03.005
基于推理攻击的生成模型隐私风险评估技术研究与应用综述
A Review of the Research and Application of Privacy Risk Assessment Techniques for Generative Models Based on Inference Attacks
摘要
Abstract
[Objective]To systematically sort out the research progress and application status of privacy risk assessment techniques for generative models based on inference attacks,[Literature Scope]this paper has surveyed more than 70 pieces of literature from mainstream conferences and jour-nals between 2015 and 2024.[Methods]From the technical dimension,the core classification basis is the assumptions of black-box and white-box conditions.Under the assumptions of black-box and white-box conditions,a detailed summary is made by further classifying the attack meth-ods for each type of generative model.From the application dimension,the focus is on the com-parison of privacy risk assessment framework solutions for synthetic data.[Results]The existing research on at-tack technologies is relatively complete.However,it has a high degree of coupling with the types of models and is limited by the accuracy rate in black-box scenarios,resulting in limitations in terms of universality and accuracy of the assessment framework for the privacy risks of synthetic data in practical applications.[Conclusion]Compared with current reviews in the same research direction,this paper for the first time summarizes the latest achievements of membership inference attacks on large language models and simultaneously conducts a comparative analysis of the current latest privacy risk assessment frameworks for synthetic data.Through a summary and analysis from both dimensions of technology and application,it provides valuable references and guidance for researchers in this direction.关键词
生成模型/成员推理攻击/属性推理攻击/隐私风险评估Key words
generative model/membership inference attack/attribute inference attack/privacy risk assessment引用本文复制引用
张宁徽,龙春,万巍,李婧,杨帆,魏金侠,付豫豪..基于推理攻击的生成模型隐私风险评估技术研究与应用综述[J].数据与计算发展前沿,2025,7(3):48-66,19.基金项目
国家重点研发计划(2023YFC3304704) （2023YFC3304704）
中国科学院网络安全和信息化专项(CAS-WX2022GC-04) （CAS-WX2022GC-04）
中国科学院青年创新促进会项目(2022170) （2022170）
