Title :
A Framework for Hybrid Fuzzy Logic Intrusion Detection Systems
Author :
El-Semary, A. ; Edmonds, Janica ; Gonzalez, Jesús ; Papa, Mauricio
Author_Institution :
Center for Inf. Security, Tulsa Univ., OK
Abstract :
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
Keywords :
Java; data mining; expert system shells; fuzzy logic; fuzzy reasoning; fuzzy set theory; security of data; FuzzyJess toolkit; Java expert system shell; Jess; anomaly-based signatures; data security; fuzzy data-mining algorithm; fuzzy logic; fuzzy reasoning; fuzzy rule extraction; fuzzy signatures; hybrid intrusion detection systems; inference engine; Councils; Engines; Expert systems; Fuzzy logic; Fuzzy sets; Inference algorithms; Intrusion detection; Java; Laboratories; Prototypes;
Conference_Titel :
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
Conference_Location :
Reno, NV
Print_ISBN :
0-7803-9159-4
DOI :
10.1109/FUZZY.2005.1452414
