Privacy-Preserving Data Aggregation in Wireless Sensor Networks
It is very challenging problem in wireless sensor networks to provide privacy preservation during data aggregation. In this paper the authors are describing two schemes that provide different approaches for privacy preservation. In the first one there are two approaches for additive aggregation functions, which can be extended to approximate MAX/MIN aggregation functions. The first scheme: Cluster-based Private Data Aggregation (CPDA) uses clustering protocols and algebraic properties of polynomials. It has the advantage of less communication overhead. The second scheme: Slice-Mix-AggRegaTe (SMART) uses slicing techniques and the associative property of addition.