Abstract
Providing efficient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this article, we present two privacy-preserving data aggregation schemes for additive aggregation functions, which can be extended to approximate MAX/MIN aggregation functions. The first scheme--- Cluster-based Private Data Aggregation (CPDA)---leverages clustering protocol and algebraic properties of polynomials. …
Authors
He W; Liu X; Nguyen HV; Nahrstedt K; Abdelzaher T
Journal
ACM Transactions on Sensor Networks, Vol. 8, No. 1, pp. 1–22
Publisher
Association for Computing Machinery (ACM)
Publication Date
8 2011
DOI
10.1145/1993042.1993048
ISSN
1550-4859