重复攻击下差分隐私保护参数ε的选取方法

doi:10.19678/j.issn.1000-3428.0048453

计算机工程 ›› 2018, Vol. 44 ›› Issue (7): 145-149. doi: 10.19678/j.issn.1000-3428.0048453

重复攻击下差分隐私保护参数ε的选取方法

郝晨艳^1a,2,3,彭长根 ^1b,2,3,4,张盼盼 ^1a,2,3

1.贵州大学 a.数学与统计学院;b.计算机科学与技术学院,贵阳 550025; 2.贵州省公共大数据重点实验室,贵阳 550025; 3.密码学与数据安全研究所,贵阳 550025; 4.广东省信息安全技术重点实验室,广州 510006

收稿日期:2017-08-24 出版日期:2018-07-15 发布日期:2018-07-15
作者简介:郝晨艳(1990—),女,硕士,主研方向为信息安全、可信计算;彭长根,教授、博士、博士生导师;张盼盼,硕士。
基金资助:
国家自然科学基金(61662009,61262073,61363068);国家密码发展基金(MMJJ20170129);广东省信息安全技术重点实验室开放课题(GDXXAQ2016-04);贵州省科技计划项目(［2016］1023,［2017］1045)。

Selection Method of Differential Privacy Protection Parameter ε Under Repeated Attack

HAO Chenyan ^1a,2,3,PENG Changgen ^1b,2,3,4,ZHANG Panpan ^1a,2,3

1a.College of Mathematics and Statistics;1b.College of Computer Science and Technology,Guizhou University,Guiyang 550025,China; 2.Guizhou Provincial Key Laboratory of Public Big Data,Guiyang 550025,China; 3.Institute of Cryptography and Data Security,Guiyang 550025,China; 4.Guangdong Provincial Key Laboratory of Information Security Technology,Guangzhou 510006,China

Received:2017-08-24 Online:2018-07-15 Published:2018-07-15

摘要/Abstract

摘要：

现有差分隐私保护参数ε的选取仅考虑在给定攻击模型下,对攻击者进行一次攻击的情形,但在实际中往往涉及攻击者的连续多次攻击。为此,提出一种重复攻击下实现差分隐私保护技术安全性的攻击模型。通过对重复攻击的结果与噪音分布函数的特点进行分析,获取噪音落入容错区间的概率,结合排列组合方法,推断出攻击者攻击成功的概率,进而得到参数ε的选取范围。实验结果表明,只要给定攻击次数、容错区间和攻击者成功的概率,该模型就可以找出合适的参数ε。

关键词: 差分隐私, 重复攻击, 随机算法, 攻击模型, 数据隐私

Abstract:

The published literature on the selection of differential privacy protection parameter ε focuses on only one time attack of data-sets by attackers,while in practice it frequently involves the attacker’s repeated attacks.In view of this,a measure model under repeated attacks is proposed.The probability that the noise falls into the fault-tolerant interval is obtained by analyzing the results of the repeated attack and the characteristics of noise distribution function.Combining with the method of permutation and combination,it infers the attacker’s probability of successful attack,further obtains the selection range of the parameter ε.Experimental results show that,when given the number of attacks,the fault-tolerance interval and the probability of the attacker’s success,the proposed model can always find the appropriate parameter ε.

Key words: differential privacy, repeated attack, random algorithm, attack model, data privacy

中图分类号:

TP311

郝晨艳,彭长根,张盼盼. 重复攻击下差分隐私保护参数ε的选取方法[J]. 计算机工程, 2018, 44(7): 145-149.

HAO Chenyan,PENG Changgen,ZHANG Panpan. Selection Method of Differential Privacy Protection Parameter ε Under Repeated Attack[J]. Computer Engineering, 2018, 44(7): 145-149.

http://www.ecice06.com/CN/Y2018/V44/I7/145

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