AI Enhanced Automatic Response System for Resisting Network Threats

Abstract

Network threats are malicious attacks that endanger network security. With terabits of information stored in the network and much of this information being confidential, cyber security turns to be very important. Most network protection mechanisms are based on firewall and Intrusion Detection System (IDS). However, with the diversification of cyber-attacks, traditional defense mechanisms cannot fully guarantee the security of the network. In this paper, we propose an automatic network threat response system based on machine learning and deep learning. It comprises three sub-modules: threat detection module, threat identification module and threat mitigation module. The experimental results show that the proposed system can handle 22 types of network threats in the KDD99 dataset and the rate of successful response is over 97%, which is much better than the traditional ways.