Expressive and Deployable Swarm Intelligence Based Cybersecurity for Wireless Sensor Network

Abstract

Wireless sensor networks (WSNs) play a pivotal role in Cyber Physical Systems (CPSs), particularly for operations such as observing the location and monitoring it. To enhance the cyber security in WSN-enabled CPSs, various researchers have proposed a various category of algorithms, inspired by biological phenomena. These algorithm works on the basis of mobility of head node (Mobile Anchor Node). However, these WSNs mobile anchor node are subject to various types of optimization like Grey wolf optimizer (GWO) and Whale optimization Algorithm (WOA). Complexity is one of the limitation of these algorithm and also it is vulnerable to damage, theft, or destruction of sensitive data, in addition to that interference in services also occur in CPSs. To prevent these cyber-attack, we proposed generic bio-inspired model ie., enhanced Grey wolf optimizer path planning called Swarm Intelligence for WSN Cyber security that addresses drawbacks of prior bio-inspired approaches. In this model WSN enabled Cyber Physical Systems use ID-Based Aggregate Signature Scheme to detect the cyber-attack and keep data integrity