An energy efficient hybrid dnn based intrusion detection using imeac dep in wsn

Abstract

Recent improvements in low-power Sensor Nodes (SNs) that have newlinebeen merged with wireless communication methods have spawned the field of newlineWireless Sensor Networks (WSN), which has numerous data collection and newlinetracking applications. Considering that WSNs are frequently installed in harsh newlineand inaccessible areas, it is crucial to build an energy-efficient and secure newlinesystems. The security of Wireless Sensor Networks requires a Network newlineIntrusion Detection System (NIDS) nowadays. The classic NIDS paradigm newlinemet major limits with network traffic data as a result of the growing newlinecomplexity of contemporary attacks. These limitations have an immediate newlineimpact on the overall performance of the WSN. Due to the fact that WSN data newlinetransmission occurs across wireless networks, security becomes a major newlineproblem, and safe routing techniques must be devised. Clustering is an newlineefficient technique for increasing the life of a Wireless Sensor Network newline(WSN). This research introduces a novel Intelligent Metaheuristics-Based newlineEnergy-Aware Clustering With Data Encryption Protocol (IMEAC-DEP) for newlineWSN to increase the energy efficiency of WSN. The goal of the IMEAC-DEP newlineapproach is to choose an appropriate set of CHs to encrypt data for newlineinter-cluster communication. The two principal phases of the proposed newlineIMEAC-DEP model are clustering and data encryption. In the initial stage, newlinefour fitness factors are employed to generate a new Chimp Optimization newlineAlgorithm-Based Clustering (COA-C) approach. Next, in the second stage, an newlineSC-AFSA-based data encryption technique is derived. The primary objective newlineof the Chimp Optimization Algorithm-based Energy Aware Secure Routing newlineProtocol (COA-EASRP) technique is to derive optimal routes in WSN. newline