Efficient Handling of Adversary Attacks in Aggregation Applications
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Current approaches to handling adversary attacks against data aggregation in sensor networks either aim exclusively at the detection of aggregate data corruption or provide rather inefficient ways to identify the nodes captured by an adversary. In contrast, we propose a distributed algorithm for efficient identification of captured nodes over a constant number of rounds, for an arbitrary number of captured nodes. We formulate our problem as a combinatorial group testing problem and show that this formulation leads not only to efficient identification of captured nodes but also to a precise cost-based characterization of when in-network aggregation retains its assumed benefits in a sensor network operating under persistent attacks.