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Superb: Superior Behavior-Based Anomaly Detection Defining Authorized Users' Traffic Patterns, Daniel Karasek
Superb: Superior Behavior-Based Anomaly Detection Defining Authorized Users' Traffic Patterns, Daniel Karasek
Master of Science in Computer Science Theses
Network anomalies are correlated to activities that deviate from regular behavior patterns in a network, and they are undetectable until their actions are defined as malicious. Current work in network anomaly detection includes network-based and host-based intrusion detection systems. However, network anomaly detection schemes can suffer from high false detection rates due to the base rate fallacy. When the detection rate is less than the false positive rate, which is found in network anomaly detection schemes working with live data, a high false detection rate can occur. To overcome such a drawback, this paper proposes a superior behavior-based anomaly detection …