Self-adaptive web intrusion detection system - Institut Agro Rennes-Angers Accéder directement au contenu
Rapport (Rapport De Recherche) Année : 2009

Self-adaptive web intrusion detection system

Résumé

The evolution of the web server contents and the emergence of new kinds of intrusions make necessary the adaptation of the intrusion detection systems (IDS). Nowadays, the adaptation of the IDS requires manual -- tedious and unreactive -- actions from system administrators. In this paper, we present a self-adaptive intrusion detection system which relies on a set of local model-based diagnosers. The redundancy of diagnoses is exploited, online, by a meta-diagnoser to check the consistency of computed partial diagnoses, and to trigger the adaptation of defective diagnoser models (or signatures) in case of inconsistency. This system is applied to the intrusion detection from a stream of HTTP requests. Our results show that our system 1) detects intrusion occurrences sensitively and precisely, 2) accurately self-adapts diagnoser model, thus improving its detection accuracy.
Fichier principal
Vignette du fichier
RR-6989.pdf (555.63 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

inria-00406450 , version 1 (22-07-2009)

Identifiants

  • HAL Id : inria-00406450 , version 1
  • ARXIV : 0907.3819

Citer

Thomas Guyet, René Quiniou, Wei Wang, Marie-Odile Cordier. Self-adaptive web intrusion detection system. [Research Report] RR-6989, INRIA. 2009, pp.24. ⟨inria-00406450⟩
433 Consultations
2306 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More