Implementation of Fruit Fly Optimization Algorithm (FFOA) to escalate the attacking efficiency of node capture attack in Wireless Sensor Networks (WSN)

Wireless sensor network (WSN) is a group of a huge number of low price, low control, and self-organizing specialized sensor nodes. WSN is very much vulnerable to different types of physical attacks due to limited resource capacity and screened to external atmosphere for circulating data. The node capture attack is one of the major attacks in WSN in which the intruder physically captures the node and remove the secret information from the node's memory. We propose a Fruit Fly Optimization Algorithm (FFOA) that is based on multiple objectives node capture attack algorithm which consists of several objectives: maximum node contribution, maximum key contribution, and least resource expenses to discover optimal nodes. It will influence an inclusive tool to demolish maximum part of the network along with effective cost and maximum attacking efficiency. The simulation result illustrates that FFOA obtains a maximum fraction of compromised traffic, lower attacking rounds, and lower energy cost as compared with Genetic Algorithm (GA) and other node capture attack algorithms. Therefore, FFOA gives maximum attacking efficiency than GA and other algorithms by capturing minimum nodes that compromise the whole network.