An enhanced security framework for IoT environment using Jaya optimisation-based genetic algorithm

Abstract

The internet of things (IoT) employs a cloud network, and the data stored in the cloud servers are highly vulnerable to various attacks. As per the current analysis report, around 23% of IoT devices are prone to attack. The data stored in the cloud storage are highly vulnerable to attacks leading to a pullback factor of 15% in economic growth. Considering the above security of the IoT devices, this paper proposes a framework integrating the Jaya algorithm and genetic algorithm to achieve an optimal detection of intrusion in the IoT network. The JA is a parameter less algorithm that does not require any precise control parameters. In contrast, the GA is a meta-heuristic approach that produces reasonable quality solutions for complex functions. The extensive analysis of the proposed algorithm yield better performance in vital parameters like accuracy, recall and F-score.