SDDA: Sparse and dynamic in-network data aggregation in sensor nets

In-network data aggregation is an effective method to reduce the amount of data transmitted and therefore saves energy consumption in sensor networks. However, data aggregation removes the integrity of original data and thus increases the damage of data falsification attack. This paper proposes four new methods that select a subset of nodes as aggregators in a sparse and dynamic fashion to frustrate the adversary. The criteria for selecting aggregators include security risk, aggregation efficiency gain, and trust relationship among nodes. Simulation results are presented that demonstrate the new methods can effectively make tradeoffs between security risk and communications cost.