Intrusion Detection System using Neural Networks

About the Project

This project delves into a comparative analysis of various neural network types employed in Intrusion Detection Systems (IDS). With the goal of enhancing network security and identifying potential threats, we explore the effectiveness of different neural network architectures. In this study, we have conducted a comprehensive comparison among three primary neural network types for intrusion detection: Shallow Neural Network, Deep Neural Network and Convolutional Neural Network.