Optimized secure and energy-efficient approach for IoT-enabled wireless sensor networks

Abstract

Wireless communication is pivotal in the modern era, enabling seamless connectivity across diverse applications. However, the increasing complexity and sophistication of cyber threats pose significant challenges to the security of wireless communication systems. This paper proposes an innovative approach to enhance wireless communication security through integrating artificial intelligence (AI) techniques. First, we construct the network using the Horizontal Partitioning Sierpinski Triangle to reduce the network's high traffic and perform the authentication process. After successful authentication, we perform the clustering process and Game Theory-Driven Clustering (GT-DC) allows nodes to strategically optimize energy utilization while forming clusters as rational entities in a cooperative game. Perform the beacon injection and detect the attacks using the Improved Random Forest (IRF) that signifies the accurate identification of cyber-attacks, IRF is improving the Bootstrap Sampling, Class Weights, and Anomaly Score Threshold. In Routing implement Improved Cache LEACH Protocol (ICLP) which discovers the effective routing establishing the Cache nodes (Cn), to obtain optimal routing by lowering latency, improving data access, enhancing data reliability, and reducing data redundancy. The proposed work is compared with evaluation metrics such as authentication time, throughput, attack detection rate, energy consumption, packet delivery rate, and delay.