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

fYear

2005

fDate

25-25 May 2005

Firstpage

325

Lastpage

330

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on

Conference_Location

Reno, NV

Print_ISBN

0-7803-9159-4

Type

conf

DOI

10.1109/FUZZY.2005.1452414

Filename

1452414