差分隐私研究进展综述  

Review of Differential Privacy Research

作　　者：赵禹齐 杨敏[1] ZHAO Yuqi;YANG Min(Key Laboratory of Aerospace Information Security and Trusted Computing,Ministry of Education,School of Cyber Science and Engineering,Wuhan University,Wuhan 430072,China)

机构地区：[1]空天信息安全与可信计算教育部重点实验室(武汉大学国家网络安全学院),武汉430072

出　　处：《计算机科学》2023年第4期265-276,共12页Computer Science

基　　金：国家自然科学基金(62172308);国家重点基础研究发展计划(2021YFB2700200)。

摘　　要：在过去的十年里,普遍的数据收集已经成为常态。随着大规模数据分析和机器学习的快速发展,数据隐私正面临着根本性的挑战。探索隐私保护和数据收集与分析之间的权衡是一个关键的科学问题。差分隐私已经成为实际上的数据隐私标准并得到了广泛的研究与应用,该技术可通过一定的随机化机制为用户数据提供严格的隐私保护。文中给出了差分隐私技术的全面概述,总结并分析了差分隐私的最新进展。具体来说,首先给出了差分隐私的理论总结,包括中心化模型、本地化模型和近年提出的洗牌模型,并对它们作了详细比较,分析了不同模型的优势和缺点。接着,在3个模型的基础上,从算法的角度介绍并分析了文献中一些典型的差分隐私机制,然后介绍了当前差分隐私技术在多个领域的应用。最后介绍了一些关于差分隐私的新研究课题,它们为差分隐私技术拓展了丰富的研究方向。In the past decade,widespread data collection has become the norm.With the rapid development of large-scale data analysis and machine learning,data privacy is facing fundamental challenges.Exploring the trade-offs between privacy protection and data collection and analysis is a key scientific question.Differential privacy has become a de facto data privacy standard and has been widely studied and applied.Differential privacy technology can provide strict privacy protection for user data through a certain randomization mechanism.This paper provides a comprehensive overview of differential privacy technology and a summary and analysis of the latest progress of differential privacy.Specifically,this paper first gives a theoretical summary of differential privacy,including the central model,the local model and the shuffle model proposed in recent years.The three models are compared,and the advantages and disadvantages of different models are analyzed.Then,on the basis of the three models,some typical differential privacy mechanisms in literatures are analyzed from the perspective of algorithms.Then the current application of differential privacy technology in various fields is introduced.Finally,some new research topics about differential privacy technology are introduced,which expand the rich research direction for differential privacy technology.

关 键 词：差分隐私 隐私保护 统计查询 洗牌模型 随机化机制 误差界 

分 类 号：TP309.2[自动化与计算机技术—计算机系统结构]