Intelligent intrusion detection system
Keum-Chang Lee, L. Mikhailov · 2004
An intrusion detection system (IDS) entails a sophisticated decision process, which involves a number of factors implicating dizziness and vagueness. We propose a new approach to the development of intelligent IDSs for misuse detection, based on pattern recognition and fuzzy classification principles. A new method for the development of fuzzy intrusion classifiers is proposed, which extracts fuzzy classification rules from numerical data, applying a heuristic learning procedure. The proposed approach to synthesis of intelligent IDSs is tested experimentally with real data. The experimental results show that the fuzzy intrusion classifier successfully detects and classifies various types of security attacks.