Ensemble learning for Intrusion Detection in Computer Networks

The security of computer networks plays a strategic role in modern computer systems. In order to enforce high protection levels against threats, a number of software tools are currently developed. Intrusion Detection Systems aim at detecting intruder who eluded the "first line" protection. In this paper, a pattern recognition approach to network intrusion detection based on ensemble learning paradigms is proposed. The potentialities of such an approach for data fusion and some open issues are outlined