Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Alert correlation systems are post-processing modules that enable intrusion analysts to find important alerts and filter false positives efficiently from the output of Intrusion...
Abstract--The Internet explosion and the increase in crucial web applications such as ebanking and e-commerce, make essential the need for network security tools. One of such tools...
Data mining for intrusion detection can be divided into several sub-topics, among which unsupervised clustering has controversial properties. Unsupervised clustering for intrusion...
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...