IEEE Communications Surveys & Tutorials · 2013 · 1.3K citations · 184 references
ComputingComputer ScienceCybersecurityComputer SecurityNetwork SecuritySecurity ArchitectureAnomaly DetectionComputer IntrusionIntrusion AnalysisIntrusion DetectionIntrusion PreventionNetwork Traffic AnalysisAnomaly Detection In CybersecurityAnomaly-based DetectionMachine Learning For Intrusion DetectionNetwork Anomaly DetectionNetwork Intrusion DetectionNetwork Traffic Anomaly DetectionNetwork-based Intrusion DetectionOverview
Network anomaly detection is an important and dynamic research area. Many network intrusion detection methods and systems (NIDS) have been proposed in the literature. In this paper, we provide a structured and comprehensive overview of various facets of network anomaly detection so that a researcher can become quickly familiar with every aspect of network anomaly detection. We present attacks normally encountered by network intrusion detection systems. We categorize existing network anomaly detection methods and systems based on the underlying computational techniques used. Within this framework, we briefly describe and compare a large number of network anomaly detection methods and systems. In addition, we also discuss tools that can be used by network defenders and datasets that researchers in network anomaly detection can use. We also highlight research directions in network anomaly detection.
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Classification and Regression Trees.
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