Metacognition in software agents using classifier systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Handbook of Evolutionary Computation
Handbook of Evolutionary Computation
Evolutionary Algorithms in Engineering Applications
Evolutionary Algorithms in Engineering Applications
A Novel Fuzzy Anomaly Detection Algorithm Based on Artificial Immune System
HPCASIA '05 Proceedings of the Eighth International Conference on High-Performance Computing in Asia-Pacific Region
Detecting Denial-of-Service attacks using the wavelet transform
Computer Communications
The use of artificial intelligence based techniques for intrusion detection: a review
Artificial Intelligence Review
Using genetic algorithm for network status learning and worm virus detection scheme
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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The paper describes the design of a genetic classifier-based intrusion detection system, which can provide active detection and automated responses during intrusions. It is designed to be a sense and response system that can monitor various activities on the network (i.e. looks for changes such as malfunctions, faults, abnormalities, misuse, deviations, intrusions, etc.). In particular, it simultaneously monitors networked computer's activities at different levels (such as user level, system level, process level and packet level) and use a genetic classifier system in order to determine a specific action in case of any security violation. The objective is to find correlation among the deviated values (from normal) of monitored parameters to determine the type of intrusion and to generate an action accordingly. We performed some experiments to evolve set of decision rules based on the significance of monitored parameters in Unix environment, and tested for validation.