Towards better selective forwarding and delay attacks detection in wireless sensor networks

A number of intrusion detection techniques have been proposed to detect different kinds of active attacks on wireless sensor networks (WSNs). Selective forwarding and delay attacks are two simple but effective attacks that can disrupt the communication in WSNs. We propose two parametrized collaborative intrusion detection techniques and optimize their parameters for given scenarios using extensive simulations and multiobjective evolutionary algorithms. Moreover, we sample the whole search space to enable evaluation of evolution performance. We evaluate the influence of changes of the number of malicious nodes on the intrusion detection performance.