Intrusion attempts due to self-propagating code are becoming an increasingly urgent problem, in part due to the homogeneous makeup of the internet. Recent advances in anomalybased...
Denver Dash, Branislav Kveton, John Mark Agosta, E...
Classifying nodes in networks is a task with a wide range of applications. It can be particularly useful in anomaly and fraud detection. Many resources are invested in the task of...
Mary McGlohon, Stephen Bay, Markus G. Anderle, Dav...
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
Abstract—We describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in ...
Wei Xu, Ling Huang, Armando Fox, David Patterson, ...
This paper presents a new spectral template-matching approach to countering shrew distributed denial-of-service (DDoS) attacks. These attacks are stealthy, periodic, pulsing, and ...