A New Efficient Defense Strategy against Byzantine Attack in Wireless Sensor Networks

Wireless sensor networks’ characteristics and limitations have led to severe challenges in their security. In this paper, one of the most common attacks, named as the Byzantine attack, has been studied. A sensor network with a mobile data fusion center is considered, and an optimized data collecting method is proposed which can apply the Neyman-Pearson criterion in a particular case of hard decision making. It means that keeping the false alarm rate constant, the detection probability is maximized. Using statistical data analysis, a closed model is obtained with an acceptable speed of convergence in a various number of sensors and attackers in the network. Then a novel malicious sensor detection scheme is exploited to identify the attack strength using the Hamming distance between every sensor report and the final decision. The simulation results show the superior performance of applying the proposed method in the decision process and also the proposed attack detection method in comparison with the conventional methods.