Enhancement of Level of Security using Wireshark Through Continuous Monitoring and Detection System

We suggest using edge computing to install an intrusion detection system (IDS) at the network edge in order to address the problem of intrusion detection in wireless sensor networks (WSNs). This IDS functions as a proactive defence system designed specifically with WSNs in mind. Our method combines an arithmetic optimisation algorithm (AOA) with Wireshark and machine learning to create an edge intelligence framework for identifying denial-of-service (DoS) assaults in wireless sensor networks (WSNs). We use the wireshark for optimisation adjustment and a parallel strategy to promote communication between populations in order to increase model accuracy. Our model achieves $\mathbf{9 8 . 9 \%}$ accuracy (ACC) through simulated studies utilising the IDS dataset in Matlab2018b. The effectiveness and practical significance of our suggested intrusion detection approach are highlighted by these experimental results.