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 ...
With the continuous evolution of the types of attacks against computer networks, traditional intrusion detection systems, based on pattern matching and static signatures, are incr...
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...
This paper presents a novel approach for detecting network intrusions based on a competitive learning neural network. In the paper, the performance of this approach is compared to...