Fruit Fly Optimization-Based Adversarial Modeling for Securing Wireless Sensor Networks (WSN)

Abstract

Node capture attack is one of the crucial attacks in wireless sensor networks (WSN) that seizes the node physically and withdraws the confidential data from the node's memory. The chapter exploits the adversarial behavior during a node capture to build an attack model. The authors also propose a fruit fly optimization algorithm (FFOA) that is a multi-objective optimization algorithm that consists of a number of objectives for capturing a node in the network: maximum node contribution, maximum key contributions are some examples of the same. The aim is to demolish the maximum part of the network while minimizing the cost and maximizing attacking efficiency. Due to the multi-objective function, the authors attain a maximum fraction of compromised traffic, lower attacking rounds, and lower energy cost as contrasted with other node capture attack algorithms. They have developed an algorithm, which is an enhanced version of FFOA and has even better efficiency than FFOA.