参与式感知中可验证的隐私保护数据类型匹配方案  

Verifiable privacy-preserving data type matching in participatory sensing

作　　者：刘梦君[1,2] 刘树波 丁永刚[1,3] Liu Mengjun;Liu Shubo;Ding Yonggang(a.School of Education,b.School of Computer Information Engineering,Hubei University,Wuhan 430062,China;School of Compu-ter,Wuhan University,Wuhan 430072,China)

机构地区：[1]湖北大学教育学院,武汉430062 [2]湖北大学计算机与信息工程学院,武汉430062 [3]武汉大学计算机学院,武汉430072

出　　处：《计算机应用研究》2018年第7期2143-2147,2152,共6页Application Research of Computers

基　　金：国家自然科学基金面上项目(41671443);武汉市科技局应用基础研究计划资助项目(2016010101010024)

摘　　要：针对参与式感知设备资源有限,很难在高效地保护用户数据类型匹配过程隐私性的同时,对匹配结果进行验证的问题,提出了一个匹配结果可验证的数据类型高效匹配方案。通过引入时空性价比高的布隆过滤器和基于位运算的门限秘密共享机制,分别解决了匹配过程隐私泄露和匹配结果不能被高效验证的问题。集中的理论分析和实验结果证实了方案的正确性、隐私保护性、可验证性和高效性。In participatory sensing,it was a great challenge to privately and efficiently pre-match the type of their sensed data with each other,while verified the matching results,due to the limited resource of devices. Thus,this paper proposed an efficient verifiable privacy-preserving data type matching scheme to tackle this challenge. It solved the above two problems with the cost-effective Bloom filter and binary secret-share scheme respectively. The correctness,privacy,efficiency of the proposed solution is testified by intensive security analysis,performance analysis,as well as simulation results.

关 键 词：参与式感知 移动社交 用户隐私 可验证性 

分 类 号：TP309.2[自动化与计算机技术—计算机系统结构]