Abstract
Due to the strict energy limitation and the common vulnerability of WSNs, providing efficient and security 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 due to the open wireless medium. To thwart traffic analysis/flow tracing and realize privacy preservation, this paper proposes a novel Efficient Privacy-Preserving Compressive Data Gathering Scheme which exploits homomorphic encryption functions in compressive data gathering. With homomorphic encryption on the compressive sensing encoded sensory reading messages, the proposed scheme offers two significant privacy-preserving features, message flow untraceability and message content confidentiality, for efficiently thwarting the traffic analysis attacks. Extensive performance evaluations and security analysis demonstrate the validity and efficiency of the proposed scheme.
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Acknowledgments
The work is supported by the open Foundation of State key Laboratory of Networking and Switching Technology (Beijing University of Posts and Telecommunications) under Grant No. SKLNST-2013-1-04, the Prospective Research Project on Future Networks (Jiangsu Future Networks Innovation Institute) under Grant No. BY2013095-4-06, the National Natural Science Foundation of China under Grant Nos. 61572184, 61472283, 61271185, 61173167, and 61472131, U.S. National Science Foundation under Grant Nos. ECCS-1231800 and CNS 1247924.
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Xie, K. et al. (2015). An Efficient Privacy-Preserving Compressive Data Gathering Scheme in WSNs. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9528. Springer, Cham. https://doi.org/10.1007/978-3-319-27119-4_49
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DOI: https://doi.org/10.1007/978-3-319-27119-4_49
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