DocumentCode
3110357
Title
Intrusion Detection via Fuzzy-Genetic Algorithm Combination with Evolutionary Algorithms
Author
Haghighat, A.T. ; Esmaeih, M. ; Saremi, A. ; Mousavi, V.R.
Author_Institution
Shahid Beheshti Univ., Tehran
fYear
2007
fDate
11-13 July 2007
Firstpage
587
Lastpage
591
Abstract
In this paper with the use of fuzzy genetic algorithm combination with evolutionary algorithms, as a method for local searching, it has been tried to exploit high capabilities of genetic algorithm, as a search algorithm, beside to other evolutionary algorithms, as local search algorithms, in order to increase efficiency of a rule learning system. For this purpose three hybrid algorithms have been used for solving the intrusion detection problem. These three algorithms are combination of genetic algorithm and SFL and PSO as three evolutionary algorithms which try to introduce efficient solutions for complex optimization problems by patterning from natural treatments.
Keywords
computer networks; fuzzy reasoning; fuzzy set theory; genetic algorithms; particle swarm optimisation; search problems; telecommunication security; PSO; computer network; evolutionary algorithm; fuzzy-genetic algorithm; intrusion detection; local search method; particle swarm optimisation; rule learning system; Data mining; Evolutionary computation; Fuzzy systems; Genetic algorithms; Genetic engineering; Intrusion detection; Iterative algorithms; Learning systems; Local area networks; TCPIP;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Science, 2007. ICIS 2007. 6th IEEE/ACIS International Conference on
Conference_Location
Melbourne, Qld.
Print_ISBN
0-7695-2841-4
Type
conf
DOI
10.1109/ICIS.2007.124
Filename
4276445
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