Abstract. This paper proposes a new approach to detecting aggregated anomalous events by correlating host file system changes across space and time. Our approach is based on a key...
Yinglian Xie, Hyang-Ah Kim, David R. O'Hallaron, M...
Hosts infected with malicious software, so called malware, are ubiquitous in today’s computer networks. The means whereby malware can infiltrate a network are manifold and rang...
Konrad Rieck, Guido Schwenk, Tobias Limmer, Thorst...
The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in...
High-speed packet content inspection and filtering devices rely on a fast multi-pattern matching algorithm which is used to detect predefined keywords or signatures in the packets....
Anomaly detection systems largely depend on user profile data to be able to detect deviation from normal activity. Most of this profile data is based on commands executed by use...