: Service platforms using text-based protocols need to be protected against attacks. Machine-learning algorithms with pattern matching can be used to detect even previously unknown...
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Abstract. In this paper, we propose a new unsupervised anomaly detection framework for detecting network intrusions online. The framework consists of new anomalousness metrics name...
The increasing complexity of cellular radio networks yields new demands concerning network security. Especially the task of detecting, repulsing and preventing abuse both by in- a...
The task in the computer security domain of anomaly detection is to characterize the behaviors of a computer user (the `valid', or `normal' user) so that unusual occurre...