Prevention of Byzantine Attack by Large Wireless Sensor Network

This paper explores reliable data fusion in mobile access wireless sensor networks under Byzantine attacks. The q-out-of-m rule, which is popular in distributed detection and can achieve a good trade-off between the miss detection probability and the false alarm rate. However, a major limitation with it is that the optimal schema parameters can only be obtained through exhaustive search, making it infeasible for large networks. In this paper, first, by exploiting the linear relationship between the schema parameters and the network size, proposed simple but effective sub-optimal linear approaches. Second, for better flexibility and scalability and derive a near-optimal closed-form solution based on the central limit theorem. Third, subjecting to a miss detection constrain, prove that the false alarm rate of q-out-of-m diminishes exponentially as the network size increase, even if the percentage of malicious nodes remains fixed. Finally, propose an effective malicious node detection schema for adaptive data fusion under time-varying attacks; the proposed schema is analyzed using the entropy-based trust model, and shown to be optimal from the information theory point of view. The proposed approaches under both static and dynamic attacks.