A Distributed Efficient Algorithm for Self-Protection of Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been widely leveraged for military and surveillance applications. Each node in a WSN plays a critical role and it can be targeted for the attackers of the network. Thus, it is required to preserve a certain level of protection for each node while exploiting the nodes for the global goals of the network. The self-protection problem focuses on scenarios that sensor nodes should protect themselves instead of protecting a set of event or objects in order to resist against any types of attacks to the nodes. Choosing a set of proper nodes to maintain self-protection requirements is an NP-Complete problem. In this paper, we devise a distributed learning automaton-based algorithm to select a subset of nodes in the network so that each node is under protection of at least one active node. The pooled simulation results validate the effectiveness of our algorithm in selecting nodes and prove that it acts better than state-of- the-art competing algorithms in term of efficiency by using a small number of nodes to provision the self-protection requirements.