Development of AI-based Intrusion Detection System with Real-Time Flow Feature Extraction

Artificial intelligence (AI) based intrusion detection system (IDS) leverages machine learning and deep learning algorithms to analyze and identify patterns that may indicate malicious behavior. Achieving real-time operation in AI-based IDS involves a tradeoff between inspection performance and the complexity of feature extraction, influenced by the duration of traffic flow observation. To reduce the delay in feature extraction, we developed an AI-based IDS with parallel traffic feature processes utilizing off-the-shelf computing devices. The proposed AI-based IDS can process traffic flows and conduct inspections at a rate of 2,800 flows per second.