TY - GEN
T1 - PDA
T2 - IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications
AU - He, Wenbo
AU - Liu, Xue
AU - Nguyen, Hoang
AU - Nahrstedt, Klara
AU - Abdelzaher, Tarek
PY - 2007
Y1 - 2007
N2 - Providing efficient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this paper, we present two privacy-preserving data aggregation schemes for additive aggregation functions. The first scheme - Cluster-based Private Data Aggregation (CPDA)-leverages clustering protocol and algebraic properties of polynomials. It has the advantage of incurring less communication overhead. The second scheme - Slice-Mix-AggRegaTe (SMART)-builds on slicing techniques and the associative property of addition. It has the advantage of incurring less computation overhead. The goal of our work is to bridge the gap between collaborative data collection by wireless sensor networks and data privacy. We assess the two schemes by privacy-preservation efficacy, communication overhead, and data aggregation accuracy. We present simulation results of our schemes and compare their performance to a typical data aggregation scheme - TAG, where no data privacy protection is provided. Results show the efficacy and efficiency of our schemes. To the best of our knowledge, this paper is among the first on privacy-preserving data aggregation in wireless sensor networks.
AB - Providing efficient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this paper, we present two privacy-preserving data aggregation schemes for additive aggregation functions. The first scheme - Cluster-based Private Data Aggregation (CPDA)-leverages clustering protocol and algebraic properties of polynomials. It has the advantage of incurring less communication overhead. The second scheme - Slice-Mix-AggRegaTe (SMART)-builds on slicing techniques and the associative property of addition. It has the advantage of incurring less computation overhead. The goal of our work is to bridge the gap between collaborative data collection by wireless sensor networks and data privacy. We assess the two schemes by privacy-preservation efficacy, communication overhead, and data aggregation accuracy. We present simulation results of our schemes and compare their performance to a typical data aggregation scheme - TAG, where no data privacy protection is provided. Results show the efficacy and efficiency of our schemes. To the best of our knowledge, this paper is among the first on privacy-preserving data aggregation in wireless sensor networks.
UR - http://www.scopus.com/inward/record.url?scp=34548301953&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34548301953&partnerID=8YFLogxK
U2 - 10.1109/INFCOM.2007.237
DO - 10.1109/INFCOM.2007.237
M3 - Conference contribution
AN - SCOPUS:34548301953
SN - 1424410479
SN - 9781424410477
T3 - Proceedings - IEEE INFOCOM
SP - 2045
EP - 2053
BT - Proceedings - IEEE INFOCOM 2007
Y2 - 6 May 2007 through 12 May 2007
ER -