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Sensors 2017, 17(2), 300; doi:10.3390/s17020300

RiPPAS: A Ring-Based Privacy-Preserving Aggregation Scheme in Wireless Sensor Networks

1
College of Computer Science & Technology, Harbin Engineering University, Harbin 150001, China
2
Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Dongkyun Kim, Houbing Song, Juan-Carlos Cano, Wei Wang, Waleed Ejaz and Qinghe Du
Received: 28 October 2016 / Revised: 16 January 2017 / Accepted: 26 January 2017 / Published: 7 February 2017
View Full-Text   |   Download PDF [618 KB, uploaded 7 February 2017]   |  

Abstract

Recently, data privacy in wireless sensor networks (WSNs) has been paid increased attention. The characteristics of WSNs determine that users’ queries are mainly aggregation queries. In this paper, the problem of processing aggregation queries in WSNs with data privacy preservation is investigated. A Ring-based Privacy-Preserving Aggregation Scheme (RiPPAS) is proposed. RiPPAS adopts ring structure to perform aggregation. It uses pseudonym mechanism for anonymous communication and uses homomorphic encryption technique to add noise to the data easily to be disclosed. RiPPAS can handle both s u m ( ) queries and m i n ( ) / m a x ( ) queries, while the existing privacy-preserving aggregation methods can only deal with s u m ( ) queries. For processing s u m ( ) queries, compared with the existing methods, RiPPAS has advantages in the aspects of privacy preservation and communication efficiency, which can be proved by theoretical analysis and simulation results. For processing m i n ( ) / m a x ( ) queries, RiPPAS provides effective privacy preservation and has low communication overhead. View Full-Text
Keywords: aggregation; data privacy; wireless sensor networks; ring structure aggregation; data privacy; wireless sensor networks; ring structure
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Zhang, K.; Han, Q.; Cai, Z.; Yin, G. RiPPAS: A Ring-Based Privacy-Preserving Aggregation Scheme in Wireless Sensor Networks. Sensors 2017, 17, 300.

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