We describe our project that marries data mining together with Grid computing. Specifically, we focus on one data mining application - the Minnesota Intrusion Detection System (MIN...
Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric...
Worm detection systems have traditionally used global strategies and focused on scan rates. The noise associated with this approach requires statistical techniques and large data s...
David Dagon, Xinzhou Qin, Guofei Gu, Wenke Lee, Ju...
Malicious software—so called malware—poses a major threat to the security of computer systems. The amount and diversity of its variants render classic security defenses ineffe...
Konrad Rieck, Philipp Trinius, Carsten Willems, Th...
Commercial anti-virus software are unable to provide protection against newly launched (a.k.a “zero-day”) malware. In this paper, we propose a novel malware detection techniqu...
S. Momina Tabish, M. Zubair Shafiq, Muddassar Faro...
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...