DocumentCode
3272427
Title
Genetic Algorithm Rule Definition for Denial of Services Network Intrusion Detection
Author
Wang, Yong ; Gu, Dawu ; Tian, XiuXia ; Li, Jing
Author_Institution
Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai, China
Volume
1
fYear
2009
fDate
6-7 June 2009
Firstpage
99
Lastpage
102
Abstract
Many previous genetic algorithm methods can get much better example results in KDD cup 99 dataset. In the real intrusion detection system, the software needs update the rule even everyday. In this paper, we expand previous work and present a fitness function, propose an efficient rule generator for denial of services of network intrusion detection. We use more chromosomes with relevant features and more rule generator. As such, the rules generated by our algorithm are suitable to continuously changing misuse detection. In order to verify our approach, we tested our proposal with KDD Cup99 dataset, The experimental results show that the proposed approach is an efficient way in network intrusion detection.
Keywords
data mining; genetic algorithms; knowledge based systems; security of data; denial of service; fitness function; genetic algorithm rule definition; knowledge discovery; network intrusion detection; Biological cells; Clustering algorithms; Computational intelligence; Computer crime; Computer science; Genetic algorithms; Intrusion detection; Software systems; Support vector machine classification; Support vector machines; denial of services; genetic algorithm; network intrusion detection; rule definition;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3645-3
Type
conf
DOI
10.1109/CINC.2009.106
Filename
5231405
Link To Document