Abstract—In this paper, we develop passive network tomography techniques for inferring link-level anomalies like excessive loss rates and delay from path-level measurements. Our ...
Abstract. Creating case representations in unsupervised textual case-based reasoning applications is a challenging task because class knowledge is not available to aid selection of...
Stewart Massie, Nirmalie Wiratunga, Susan Craw, Al...
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 call stack of a program execution can be a very good information source for intrusion detection. There is no prior work on dynamically extracting information from call stack a...
Henry Hanping Feng, Oleg M. Kolesnikov, Prahlad Fo...
Abstract. This paper proposes new cognitive algorithms and mechanisms for detecting 0day attacks targeting the Internet and its communication performances and behavior. For this pu...