位置大数据中一种基于Bloom Filter的匿名保护方法

doi:10.11896/j.issn.1002-137X.2017.06.024

摘要/Abstract

摘要： 位置大数据服务应用中存在大量的用户敏感信息,针对服务中海量数据分析的隐私泄露问题,提出一种基于Bloom Filter多哈希散列编码的位置匿名保护方法。采用启发式的隐私度量技术划分匿名区来隐藏真实的位置数据,保持欧氏距离上搜索目标的邻近关系以优化空间匿名框的面积,并在划分策略中引入查询服务相似性因子以减少空间碎片的产生。在移动用户和服务器之间构建可信的第三方位置匿名服务器,能有效地模糊目标节点,从而抵御恶意的隐私攻击。理论分析和仿真实验表明,新算法能有效优化匿名空间区域,提高隐私保护程度,并在海量数据集的构建过程中具有较优的时间复杂度。

关键词: 位置大数据服务,隐私保护,位置敏感哈希,匿名区搜索

Abstract: As there exists large amounts of user’s sensitive information in the application of big data for location,a kind of anonymous location protection method was put forward in this paper,which is based on Bloom Filter with multi-Hash coding,to solve the privacy leakage in analysis of massive data.Heuristic privacy metrology divides anonymous area to hide real data of location.Keeping the search target adjacent in Euclidean distance can optimize the area of spatial anonymous box,and the introduction of similarity factor in query service for dividing policy can reduce space debris.It can effectively blurred target node,with deployment of trusted anonymous server between the mobile user and the server by third-party,to resist malicious privacy attack.Theoretical analysis and simulation results show that the new algorithm can optimize the anonymous space and improve the privacy protection effectively,and it has better time complexity in the construction of massive data sets.

Key words: Location service on big data,Privacy preserving,Locality sensitive hashing,Anonymous spatial region

刘彦,张琳. 位置大数据中一种基于Bloom Filter的匿名保护方法[J]. 计算机科学, 2017, 44(6): 144-149. https://doi.org/10.11896/j.issn.1002-137X.2017.06.024

LIU Yan and ZHANG Lin. Improved Location Anonymous Technology for Big Data Based on Bloom Filter[J]. Computer Science, 2017, 44(6): 144-149. https://doi.org/10.11896/j.issn.1002-137X.2017.06.024

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