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Decision Making For Network Health Assessment In An Intelligent Intrusion Detection System Architecture

Author

Listed:
  • AMBAREEN SIRAJ

    (Department of Computer Science & Engineering, Butler Hall, Room 300, Corner of Barr and Perry, Mississippi State University, Mississippi State, MS 39762, USA)

  • RAYFORD B. VAUGHN

    (Department of Computer Science & Engineering, Butler Hall, Room 300, Corner of Barr and Perry, Mississippi State University, Mississippi State, MS 39762, USA)

  • SUSAN M. BRIDGES

    (Department of Computer Science & Engineering, Butler Hall, Room 300, Corner of Barr and Perry, Mississippi State University, Mississippi State, MS 39762, USA)

Abstract

This paper describes the use of artificial intelligence techniques in the creation of a network-based decision engine for decision support in an Intelligent Intrusion Detection System (IIDS). In order to assess overall network health, the decision engine fuses outputs from different intrusion detection sensors serving as "experts" and then analyzes the integrated information to present an overall security view of the system for the security administrator. This paper reports on the workings of a decision engine that has been successfully embedded into the IIDS architecture being built at the Center for Computer Security Research, Mississippi State University. The decision engine uses Fuzzy Cognitive Maps (FCM)s and fuzzy rule-bases for causal knowledge acquisition and to support the causal knowledge reasoning process.

Suggested Citation

  • Ambareen Siraj & Rayford B. Vaughn & Susan M. Bridges, 2004. "Decision Making For Network Health Assessment In An Intelligent Intrusion Detection System Architecture," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 281-306.
    • Handle: RePEc:wsi:ijitdm:v:03:y:2004:i:02:n:s0219622004001057
    DOI: 10.1142/S0219622004001057
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