TY - GEN
T1 - An efficient privacy-preserving compressive data gathering scheme in WSNs
AU - Xie, Kun
AU - Ning, Xueping
AU - Wang, Xin
AU - Wen, Jigang
AU - Liu, Xiaoxiao
AU - He, Shiming
AU - Zhang, Daqiang
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
KW - Compressive sensing
KW - Homomorphic encryption function
KW - Privacy-preserving
KW - WSNs
UR - https://www.scopus.com/pages/publications/84959339583
U2 - 10.1007/978-3-319-27119-4_49
DO - 10.1007/978-3-319-27119-4_49
M3 - Conference contribution
AN - SCOPUS:84959339583
SN - 9783319271187
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 702
EP - 715
BT - Algorithms and Architectures for Parallel Processing - 15th International Conference, ICA3PP 2015, Proceedings
A2 - Perez, Gregorio Martinez
A2 - Zomaya, Albert
A2 - Wang, Guojun
A2 - Li, Kenli
PB - Springer Verlag
T2 - 15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015
Y2 - 18 November 2015 through 20 November 2015
ER -