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

  • Authors:
  • Damiano Bolzoni;Sandro Etalle;Pieter H. Hartel

  • Affiliations:
  • University of Twente, Enschede, The Netherlands;University of Twente, Enschede, The Netherlands and Eindhoven Technical University, The Netherlands;University of Twente, Enschede, The Netherlands

  • Venue:
  • RAID '09 Proceedings of the 12th International Symposium on Recent Advances in Intrusion Detection
  • Year:
  • 2009

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Abstract

Anomaly-based intrusion detection systems are usually criticized because they lack a classification of attacks, 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.