Proposing a Model for Detecting Intrusion Network Attacks Using Machine Learning Techniques

Abstract

: At the present time, the reliance on computers is increasing in all aspects of life, so it is necessary to protect computer networks and computing resources from complex attacks against the network. This is performed by building tools, applications, and systems that detect attacks or anomalies adapting to ever-changing architectures and dynamically changing threats. The goal of this paper is to build a Network Intrusion Detection System (NIDS) based on deep learning techniques such as Convolutional Neural Network (CNN), which demonstrated its efficiency in predicting, classifying, and extracting high-level features in network traffic.