Abstract : Flow-based intrusion detection will play an important role in high-speed networks, due to the stringent performance requirements of packet-based solutions. Flow monitoring technologies, such as NetFlow or IPFIX, aggregate individual packets into flows, requiring new intrusion detection algorithms to deal with the aggregated data. These algorithms are subject to constraints on real-time and accurate detection of intrusions, due to the nature of current flow monitoring technologies. In this paper, we propose a framework for flow-based intrusion detection, aiming to detect intrusions in real-time, and to be resilient against negative effects of attacks on monitoring systems. This research is still in its initial phase and will contribute to a Ph.D. thesis after four years.
Type de document :
Communication dans un congrès
Ramin Sadre; Jiří Novotný; Pavel Čeleda; Martin Waldburger; Burkhard Stiller. 6th International Conference on Autonomous Infrastructure (AIMS), Jun 2012, Luxembourg, Luxembourg. Springer, Lecture Notes in Computer Science, LNCS-7279, pp.109-112, 2012, Dependable Networks and Services. 〈10.1007/978-3-642-30633-4_13〉
https://hal.inria.fr/hal-01529793
Contributeur : Hal Ifip
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Soumis le : mercredi 31 mai 2017 - 13:17:53
Dernière modification le : jeudi 1 juin 2017 - 01:09:01
Document(s) archivé(s) le : mercredi 6 septembre 2017 - 16:15:56
Rick Hofstede, Aiko Pras. Real-Time and Resilient Intrusion Detection: A Flow-Based Approach. Ramin Sadre; Jiří Novotný; Pavel Čeleda; Martin Waldburger; Burkhard Stiller. 6th International Conference on Autonomous Infrastructure (AIMS), Jun 2012, Luxembourg, Luxembourg. Springer, Lecture Notes in Computer Science, LNCS-7279, pp.109-112, 2012, Dependable Networks and Services. 〈10.1007/978-3-642-30633-4_13〉. 〈hal-01529793〉
