Model-driven, network-context sensitive intrusion detection

Frederic Massicotte, Mathieu Couture, Lionel Briand, Yvan Labiche

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Intrusion Detection Systems (IDSs) have the reputation of generating many false positives. Recent approaches, known as stateful IDSs, take the state of communication sessions into account to address this issue. A substantial reduction of false positives, however, requires some correlation between the state of the session, known vulnerabilities, and the gathering of more network context information by the IDS than what is currently done (e.g., configuration of a node, its operating system, running applications). In this paper we present an IDS approach that attempts to decrease the number of false positives by collecting more network context and combining this information with known vulnerabilities. The approach is model-driven as it relies on the modeling of packet and network information as UML class diagrams, and the definition of intrusion detection rules as OCL expressions constraining these diagrams. The approach is evaluated using real attacks on real systems, and appears to be promising.

Original languageEnglish
Title of host publicationModel Driven Engineering Languages and Systems - 10th International Conference, MODELS 2007, Proceedings
PublisherSpringer Verlag
Pages61-75
Number of pages15
ISBN (Print)9783540752080
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event10th International Conference on Model Driven Engineering Languages and Systems, MODELS 2007 - Nashville, TN, United States
Duration: 30 Sep 20075 Oct 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4735 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Model Driven Engineering Languages and Systems, MODELS 2007
Country/TerritoryUnited States
CityNashville, TN
Period30/09/075/10/07

Keywords

  • Intrusion detection
  • OCL constraints
  • UML modeling

Fingerprint

Dive into the research topics of 'Model-driven, network-context sensitive intrusion detection'. Together they form a unique fingerprint.

Cite this