| Publisher | Institute of Electrical and Electronics Engineers | ||
|---|---|---|---|
| Format | 246.7KB PDF | Date added | 08 Dec 2003 |
| Topics | Network Security, Security Tools, Intrusion Detection Systems | ||
| Downloads | 100 | ||
Most modern intrusion detection systems employ multiple intrusion sensors to maximize their trustworthiness. The overall security view of the multi-sensor intrusion detection system can serve as an aid to appraise the trustworthiness in the system. This paper presents the research effort in that direction by describing a Decision Engine for an Intelligent Intrusion Detection System (IIDS) that fuses information from different intrusion detection sensors using an artificial intelligence technique. The Decision Engine uses Fuzzy Cognitive Maps (FCMs) and fuzzy rule-bases for causal knowledge acquisition and to support the causal knowledge reasoning process. This paper presents report on the workings of the Decision Engine that has been successfully embedded into the IIDS architecture being built at the Center for Computer Security Research (CCSR), Mississippi State University.
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