Real-Time and Resilient Intrusion Detection: A Flow-Based Approach - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2012

Real-Time and Resilient Intrusion Detection: A Flow-Based Approach

Rick Hofstede
  • Fonction : Auteur
  • PersonId : 1009103
Aiko Pras
  • Fonction : Auteur
  • PersonId : 994064

Résumé

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.
Fichier principal
Vignette du fichier
978-3-642-30633-4_13_Chapter.pdf (150.62 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01529793 , version 1 (31-05-2017)

Licence

Identifiants

Citer

Rick Hofstede, Aiko Pras. Real-Time and Resilient Intrusion Detection: A Flow-Based Approach. 6th International Conference on Autonomous Infrastructure (AIMS), Jun 2012, Luxembourg, Luxembourg. pp.109-112, ⟨10.1007/978-3-642-30633-4_13⟩. ⟨hal-01529793⟩
121 Consultations
168 Téléchargements

Altmetric

Partager

More