Integrating Artificial Intelligence into Snort IDS

Snort is an open source network intrusion detection and prevention system (IDS/IPS) utilizing a rule-driven language, its shortcoming is unable to detect new attacks. This paper explores how to integrate Artificial Intelligence into Snort IDS/IPS, which enables IDS/IPS adapt to networks and detect anomalies. As for preprocessors of Snort IDS, a learning algorithm such as artificial neural network (ANN) is integrated into it. So Artificial Intelligence alleviates some of the security professionals´ work load by first learning about a network and gauging reactions from a security professional to reduce false positives, and second, by adapting to changes in the network to identify new attacks.