Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything...
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...
Intrusion detection systems are distributed applications that analyze the events in a networked system to identify malicious behavior. The analysis is performed using a number of ...
We argue in favor of the explicit inclusion of suspicion as a concrete concept to be used in the analysis of audit data in order to guide the search for evidence of misuse. Our ap...
Our demo presents an agent-based intrusion detection system designed for deployment on high-speed backbone networks. The major contribution of the system is the integration of sev...