An Efficient Deep Learning Technique for Intrusion Detection in Wireless Sensor Network
Prity Kumari, Rakesh Kumar Tiwari · 2023
Predicting intrusion detection in a wireless sensor network (WSN) involves using machine learning algorithms to analyze network traffic data and predict whether an intrusion or security breach will occur. The goal of intrusion prediction is to provide advanced warning of potential attacks and allow for proactive measures to be taken to prevent or mitigate the attack's impact. Several machines and deep learning algorithms can be used for intrusion prediction in WSNs. This research describes a practical deep-learning approach for Intrusion Detection in WSN based on artificial neural networks. Spyder IDE of python with version 3.7 is used for the simulation work. The results of the simulations demonstrate that the anticipated model is accurate 99.99% of the time.