一种基于差分隐私的数据查询分级控制策略

doi:10.11896/jsjkx.180901690

摘要/Abstract

摘要： 在数据的查询、发布和共享过程中,保护用户的隐私数据至关重要。现有的隐私保护模型大多未考虑不同信任等级用户的查询结果不同,而为查询数据集的所有用户提供相同隐私保护级别的数据。这种“一刀切”的方法忽略了不同个体之间数据隐私保护要求的差异性。并且多个查询用户可能具有不同的查询权限和信誉值,所查询的数据隐私属性也不尽相同。因此,这些提供相同级别的隐私保护方法无法满足隐私保护的差异化需求。为此,提出一种基于差分隐私的数据查询分级控制策略。当查询用户提交查询请求时,该隐私保护策略可以根据查询者的权限、信誉值和数据隐私属性计算查询安全信任度并量化分级,对不同信任等级的查询返回结果添加服从不同分布特性的Laplace噪声以保护数据隐私。为保证高可用性的数据不被低等级查询用户获取,引入可用性评估模块,在保护隐私的同时对数据的可用性进行分析。仿真实验结果表明:所提出的查询分级控制模型能够为不同等级的查询用户提供误差率在0.1%~30%范围内的数据信息,解除了差分隐私仅提供相同级别隐私保护的重要限制,有效解决了多信任等级用户查询的隐私泄露问题。并且,对最终查询返回结果进行可用性分析能够在差分隐私保护范围内最大程度地提高数据的可用性。

关键词: 查询控制, 差分隐私, 数据可用性, 信任等级, 信任度, 隐私保护

Abstract: Protecting users’ private data is critical in the process of data querying,publishing and sharing.Most of the existing privacy protection models provide a uniform level of privacy protection for all query users of the dataset without considering the different query results of different trust levels.This “one size fits all” approach ignores the differences of the privacy protection requirements between individuals.Multiple query users may have different query privilege and reputation value,and the data privacy attributes of the queries are also different.Therefore,those methods of providing a uniform level of privacy protection cannot meet the differentiated needs of privacy protection.This paper proposed a hie-rarchical query control strategy based on differential privacy.When the query user submits a query request,this method can protect data privacy by adding Laplace noise with different distribution characteristics into the returned results for different trust levels queries.The trust levels are based on the query security trust degree according to the privilege,repu-tation value of users and data privacy attribute.In order to ensure high availability data cannot be obtained by low-level query users,the availability evaluation module is introduced to analyze the data availability while protecting privacy.The simulation experimental results demonstrate that the proposed control model can provide protected data with error rates ranging from 0.1% to 30% for different levels of query users,releasing the important limitation of differential privacy providing only a uniform level of privacy protection,and solving the privacy leakage problem of data query of multi-trust level users.And analyzing the availability of the query results can maximize data availability within the context of diffe-rential privacy protection.

Key words: Data availability, Differential privacy, Privacy preserving, Query control, Trust degree, Trust level

中图分类号:

TP309.2

李森有, 季新生, 游伟, 赵星. 一种基于差分隐私的数据查询分级控制策略[J]. 计算机科学, 2019, 46(11): 130-136. https://doi.org/10.11896/jsjkx.180901690

LI Sen-you, JI Xin-sheng, YOU Wei, ZHAO Xing. Hierarchical Control Strategy for Data Querying Based on Differential Privacy[J]. Computer Science, 2019, 46(11): 130-136. https://doi.org/10.11896/jsjkx.180901690

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