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An efficient privacy-preserving compressive data gathering scheme in WSNs

文献类型：期刊论文

作者Xie, Kun2,3; Ning, Xueping2; Wang, Xin3; He, Shiming4; Ning, Zuoting2; Liu, Xiaoxiao1; Wen, Jigang5; Qin, Zheng2
刊名INFORMATION SCIENCES
出版日期2017-06-01
卷号390页码:82-94
关键词Homomorphic encryption function Compressive sensing Privacy-preserving WSNs
ISSN号0020-0255
DOI10.1016/j.ins.2016.12.050
英文摘要Because of the strict energy limitation and the common vulnerability of Wireless Sensor Networks (WSNs), providing efficient and secure data gathering in WSNs becomes an essential problem. Compressive data gathering, which is based on the recent breakthroughs in compressive sensing theory, has been proposed as a viable approach for data gathering in WSNs at low communication overhead. Nevertheless, compressive data gathering is susceptible to various attacks in the presence of the open wireless medium. In this paper, we propose a novel Efficient Privacy-Preserving Compressive Data Gathering Scheme, which exploits homomorphic encryption functions in compressive data gathering to thwart the traffic analysis/flow tracing and realize the privacy preservation. This allows the proposed scheme to possess the two important privacy-preserving features of message flow untraceability and message content confidentiality. Extensive performance evaluations and security analyses demonstrate the validity and efficiency of the proposed scheme. (C) 2017 Elsevier Inc. All rights reserved.
资助项目Prospective Research Project on Future Networks (Jiangsu Future Networks Innovation Institute)[BY2013095-4-06] ; National Natural Science Foundation of China[61572184] ; National Natural Science Foundation of China[61300219] ; National Natural Science Foundation of China[61472283] ; National Natural Science Foundation of China[51575167] ; National Natural Science Foundation of China[61272546] ; National Natural Science Foundation of China[61472131] ; Science and Technology Key Projects of Hunan Province[2015TP1004] ; Science and Technology Key Projects of Hunan Province[2016JC2075] ; U.S. NSF CNS[1526843]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000394563300006
出版者ELSEVIER SCIENCE INC
源URL[http://119.78.100.204/handle/2XEOYT63/7376]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Xie, Kun
作者单位1.State Grid HuNan Elect Power Co, Res Inst, Changsha, Hunan, Peoples R China
2.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha, Hunan, Peoples R China
3.SUNY Stony Brook, Dept Elect & Comp Engn, Stony Brook, NY 11794 USA
4.Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Hunan Prov Key Lab Intelligent Proc Big Data Tran, Changsha, Hunan, Peoples R China
5.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714		 Xie, Kun,Ning, Xueping,Wang, Xin,et al. An efficient privacy-preserving compressive data gathering scheme in WSNs[J]. INFORMATION SCIENCES,2017,390:82-94.
APA Xie, Kun.,Ning, Xueping.,Wang, Xin.,He, Shiming.,Ning, Zuoting.,...&Qin, Zheng.(2017).An efficient privacy-preserving compressive data gathering scheme in WSNs.INFORMATION SCIENCES,390,82-94.
MLA Xie, Kun,et al."An efficient privacy-preserving compressive data gathering scheme in WSNs".INFORMATION SCIENCES 390(2017):82-94.

入库方式： OAI收割

来源：计算技术研究所

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