A blackboard-based learning intrusion detection system: A new approach

Mayukh Dass, James Cannady, Walter D. Potter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Intrusion Detection is one of the crucial real-time problems in the field of computer networking. With the changing technology and the exponential growth of Internet traffic, it is becoming difficult for any existing intrusion detection system to offer a reliable service. From earlier research, we have found that there exists a behavioral pattern in the attacks that can be learned. That is why an Artificial Neural Network is so successful in detecting network intrusions. Still, this approach is not effective in a dynamic environment where changes take place frequently. This paper proposes a blackboard-based Learning Intrusion Detection System, which is controlled by autonomous agents and has an online learning capability. This feature enables the system to adapt itself with the changing environment and to perform better than present systems.

Original languageEnglish
Title of host publicationDevelopments in Applied Artificial Intelligence
EditorsPaul W. H. Chung, Chris Hinde, Moonis Ali
PublisherSpringer-Verlag
Pages385-390
Number of pages6
ISBN (Print)3540404554, 9783540404552
DOIs
StatePublished - 2003
Event16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003 - Loughborough, United Kingdom
Duration: Jun 23 2003Jun 26 2003

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2718
ISSN (Print)0302-9743

Conference

Conference16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003
CountryUnited Kingdom
CityLoughborough
Period06/23/0306/26/03

Keywords

  • Artificial neural network
  • Autonomous agents
  • Blackboard architecture
  • Intrusion Detection
  • Network security

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  • Cite this

    Dass, M., Cannady, J., & Potter, W. D. (2003). A blackboard-based learning intrusion detection system: A new approach. In P. W. H. Chung, C. Hinde, & M. Ali (Eds.), Developments in Applied Artificial Intelligence (pp. 385-390). (Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science); Vol. 2718). Springer-Verlag. https://doi.org/10.1007/3-540-45034-3_39