移动群智感知中融合数据的隐私保护方法

王涛春; 金鑫; 吕成梅; 陈付龙; 赵传信

doi:10.7544/issn1000-1239.2020.20190579

移动群智感知中融合数据的隐私保护方法

(安徽师范大学计算机与信息学院安徽芜湖 241002) (网络与信息安全安徽省重点实验室(安徽师范大学) 安徽芜湖 241002) (wangtc@nuaa.edu.cn)

基金项目: 国家自然科学基金项目(61402014,61972439,61972438,61871412)；赛尔网络下一代互联网创新项目(NGII20170312)；安徽省教育厅高校自然科学研究重点项目(KJ2019A1164)；安徽师范大学博士启动项目(2018XJJ66)；安徽师范大学创新项目(2018XJJ114)

详细信息

中图分类号: TP391
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出版历程
- 发布日期: 2020-10-31

Privacy Preservation Method of Data Aggregation in Mobile Crowd Sensing

(School of Computer and Information, Anhui Normal University, Wuhu, Anhui 241002) (Anhui Provincial Key Laboratory of Network and Information Security(Anhui Normal University), Wuhu, Anhui 241002)

Funds: This work was supported by the National Natural Science Foundation of China (61402014, 61972439, 61972438, 61871412), the CERNET Next Generation Internet Creative Project of China (NGII20170312), the Key Program of Universities Natural Science Research of the Anhui Provincial Department of Education (KJ2019A1164), the Anhui Normal University PhD Startup Fund (2018XJJ66), and the Anhui Normal University Innovation Fund (2018XJJ114).

摘要

摘要: 随着移动智能设备的普及，群智感知得到广泛应用，也面临严重的隐私泄露问题.现有隐私保护方案一般假设第三方服务平台是可信的，而这种假设对应用场景要求较高.基于此，提出了群智感知中一种新的数据融合隐私保护算法ECPPDA(privacy preservation data aggregation algorithm based on elliptic curve cryptography).服务器将参与者随机划分成g个簇，并形成簇公钥.簇内节点通过簇公钥加密数据并融合得到簇融合结果数据.服务器通过与簇内成员协同合作得到融合结果原文，由于服务器接收到的是融合密文且密文解密需要簇内所有节点共同协作，因此服务器不能得到单个参与者的数据.此外，通过服务器对簇公钥的更新，能够方便参与者动态加入或失效.实验结果显示ECPPDA具有高安全性、低消耗、低通信、高精度的特点.
- 移动群智感知 /
- 融合数据 /
- 隐私保护 /
- 共谋攻击 /
- 簇
Abstract: Serious privacy leakage problems are on the rise with the wide application of mobile crowd sensing owing to the popularity of mobile smart devices. In general, the existing privacy protection schemes assume that the third-party service platform is credible, which therefore sets a high requirement on the application context. Based on this, the paper proposes a new privacy preservation data aggregation algorithm based on elliptic curve cryptography (ECPPDA) in mobile crowd sensing. The server randomly divides the participants into g clusters and forms respective cluster public key for each cluster. The nodes in the cluster encrypt the data through their own cluster public keys and merge the data aggregation results. The server obtains the aggregation result by cooperating with the members in the cluster. Since what the server receives is the ciphertext of aggregation and the ciphertext decryption requires all the nodes in the cluster to cooperate together, the server cannot obtain the data of a single participant. In addition, the updating of the cluster public key by the server can facilitate the participants to dynamically join or leave. The experimental result shows that ECPPDA has the characteristics of high security, low consumption, low communication and high precision.
- mobile crowd sensing /
- aggregation data /
- privacy preservation /
- collusion attack /
- cluster

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