Panacea: Automating Attack Classification for Anomaly-based Network Intrusion Detection Systems

Bolzoni, D. and Etalle, S. and Hartel, P.H. (2009) Panacea: Automating Attack Classification for Anomaly-based Network Intrusion Detection Systems. In: Recent Advances in Intrusion Detection.

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Abstract:	Anomaly-based intrusion detection systems are usually criticized because they lack a classication of attack, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an anomaly-based network intrusion detection system.
Item Type:	Conference or Workshop Item
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Distributed and Embedded Systems (DIES)
Link to this item:	http://purl.utwente.nl/publications/68138
Official URL:	http://dx.doi.org/10.1007/978-3-642-04342-0_1
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