网络与信息安全学报 ›› 2015, Vol. 1 ›› Issue (1): 58-65.doi: 10.11959/j.issn.2096-109x.2015.00008

• 学术论文 • 上一篇    下一篇

差分隐私保护下的数据分级发布机制

张文静(),李晖   

  1. 西安电子科技大学 综合业务网理论及关键技术国家重点实验室,陕西 西安 710071
  • 修回日期:2015-09-27 出版日期:2015-12-01 发布日期:2016-01-12
  • 作者简介:张文静(1988-),女,黑龙江绥化人,西安电子科技大学博士生,主要研究方向为大数据安全、隐私保护。|李晖(1968-),男,河南灵宝人,博士,西安电子科技大学教授、博士生导师,主要研究方向为密码学、无线网络安全、云计算安全、信息论与编码理论。
  • 基金资助:
    国家自然科学基金—广东联合基金资助项目(U1401251)

A differentially-private mechanism for multi-level data publishing

Wen-jing ZHANG(),Hui LI   

  1. State Key Laboratory of Integrated Services Networks,Xidian University,Xi’an 710071,China
  • Revised:2015-09-27 Online:2015-12-01 Published:2016-01-12
  • Supported by:
    The National Natural Science Foundation of China—Guangdong Provincial People’s Government of the Joint Natural Science Fund Projects(U1401251)

摘要:

隐私保护技术解决了数据发布过程中的隐私泄露问题,然而当前的数据发布技术大多只面向查询用户发布同一隐私保护级别的数据,并未考虑查询用户等级不同的情况。在所提出的满足差分隐私的数据分级发布机制中,数据发布方利用隐私预算参数不同的拉普拉斯机制对数据查询结果进行隐私保护处理,实现了输出隐私保护程度不同的查询结果。在依据付费或权限对查询用户分级后,数据发布方为等级较高(低)的查询用户发布隐私保护程度较低(高)的查询结果,使得查询用户可使用错误率较低(高)的数据,达到了隐私数据分级发布的效果。实验结果与安全性分析表明该机制在抵抗背景知识攻击的同时还可有效地实现输出错误率不同的分级查询结果。

关键词: 差分隐私, 数据分级发布, 拉普拉斯机制, 隐私保护

Abstract:

Privacy preserving technology had addressed the problem of privacy leakage during data publishing proc-ess,however,current data publishing technologies mostly focused on publishing privacy preserving data with single level,without considering some scenarios of multi-level users.Therefore,a differentially-private mechanism for multi-level data publishing was proposed.The proposed mechanism employed the Laplace mechanism with different privacy budgets to output results with different privacy protection levels.After the user’s level was determined ac-cording to the charge or privilege of that specific user,the goal that a user with high(low) level can only use the out-put result with low(high) privacy protection level which had low(high) error rate could be achieved.Finally,the evaluation results and security analysis show that our proposed framework can not only prevent from background knowledge attack,but also achieve multi-level data publishing with different error rates effectively .

Key words: differential privacy, multi-level data publishing, Laplace mechanism, privacy preserving

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