Evaluation of an adaptive genetic-based signature extraction system for network intrusion detection

@article{Shafi2011EvaluationOA,
  title={Evaluation of an adaptive genetic-based signature extraction system for network intrusion detection},
  author={Kamran Shafi and Hussein A. Abbass},
  journal={Pattern Analysis and Applications},
  year={2011},
  volume={16},
  pages={549-566}
}
Machine learning techniques are frequently applied to intrusion detection problems in various ways such as to classify normal and intrusive activities or to mine interesting intrusion patterns. Self-learning rule-based systems can relieve domain experts from the difficult task of hand crafting signatures, in addition to providing intrusion classification capabilities. To this end, a genetic-based signature learning system has been developed that can adaptively and dynamically learn signatures… CONTINUE READING