A Framework for Hybrid Fuzzy Logic Intrusion Detection Systems
Aly Mohamed El-Semary, Janica Edmonds, Jesús González, Mauricio Papa · 2005
This paper describes a framework for implementing intrusion detection systems using fuzzy logic. A fuzzy data-mining algorithm is used to extract fuzzy rules for the inference engine. The modular architecture is implemented using the Java expert system shell (Jess) and the FuzzyJess toolkit developed by Sandia National Laboratories and the National Research Council of Canada respectively. Experimental results for a hybrid prototype system using anomaly-based and fuzzy signatures are provided using data sets from MIT Lincoln Laboratory