Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically ...
Since current internet threats contain not only malicious codes like Trojan or worms, but also spyware and adware which do not have explicit illegal content, it is necessary to hav...
A low-effort data mining approach to labeling network event records in a WLAN is proposed. The problem being addressed is often observed in an AI and data mining strategy to netwo...
Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliy...
Stateful, in-depth, inline traffic analysis for intrusion detection and prevention is growing increasingly more difficult as the data rates of modern networks rise. Yet it remai...
Abstract. We apply the Unsupervised Niche Clustering (UNC), a genetic niching technique for robust and unsupervised clustering, to the intrusion detection problem. Using the normal...