基于属性基加密的用户协作连续查询隐私保护策略

发布时间：2019-03-19 08:15

【摘要】：在基于位置服务(LBS,location-based service)中,不可信的服务器可利用掌握的用户属性信息作为背景知识,在快照或连续查询过程中关联不确定位置集合中的位置,进而识别出潜在的用户真实位置造成用户位置隐私的泄露。针对这种攻击行为,当前主要的隐私保护方法是进行属性泛化。然而,已有的属性泛化方法一般假设存在一个可信的第三方服务器对参与匿名用户的属性进行寻找与比较,而这个第三方服务器很可能因为攻击焦点或服务瓶颈问题变得不再可信。针对攻击者可能使用的用户属性进行分析攻击以及第三方服务器潜在的不可信问题,提出一种基于属性基加密(CP-ABE,ciphertext policy attribute based encryption)的方法,通过用户协作完成对用户属性的匿名操作,并且整个过程中第三方服务器以及协作用户无法获知该用户任何隐私信息。最后,安全性分析和实验验证进一步证明了所提方法具有较高的隐私保护效力和算法执行效率。
[Abstract]:In location-based services (LBS,location-based service), untrusted servers can use user attribute information as background knowledge to associate locations in the set of uncertain locations during snapshots or continuous queries. Then identify the potential users real location caused by the privacy of the user location disclosure. For this kind of attack, the main privacy protection method is attribute generalization. However, existing attribute generalization methods generally assume that there is a trusted third-party server to find and compare the attributes of participating anonymous users. This third-party server is likely to become untrusted because of attack focus or service bottlenecks. In this paper, an attribute-based encryption (CP-ABE,ciphertext policy attribute based encryption) method is proposed for the analysis attacks of user attributes that may be used by attackers and the potential uncreditable problems of third-party servers. The anonymous operation of user attributes is accomplished through user cooperation, and the third-party server and the cooperative user cannot obtain any privacy information of the user during the whole process. Finally, the security analysis and experimental verification further prove that the proposed method has high privacy protection efficiency and algorithm execution efficiency.
【作者单位】：哈尔滨工程大学计算机科学与技术学院;佳木斯大学信息电子技术学院;
【基金】：国家自然科学基金资助项目(No.61472097) 高等学校博士学科点专项科研基金资助项目(No.20132304110017) 黑龙江省自然科学基金资助项目(No.F2015022)~~
【分类号】：TP309

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