An Improved PSO-Based Rule Extraction Algorithm for Intrusion Detection

Author

Chang, Zhao ; Wei-Ping, Wang

Author_Institution

Sch. of Manage., Univ. of Sci. & Technol. of China, Hefei, China

Volume

2

fYear

2009

fDate

6-7 June 2009

Firstpage

56

Lastpage

58

Abstract

The particle swarm optimization (PSO) algorithm is already proved efficient in the rule extraction in intrusion detection. But in practice the most intrusion detection systems often have a high false alarm rate. To solve it, this paper gives a new PSO-based algorithm which has a special fitness function to extract better rules set with lower false alarm rate to detect the attacks. Experiments based on the 1999 KDD cup data show that the algorithm can efficiently lower the false alarm rate.

Keywords

authorisation; particle swarm optimisation; KDD cup data; PSO-based rule extraction algorithm; false alarm rate; fitness function; intrusion detection system; particle swarm optimization; Computational intelligence; Conference management; Data mining; Decision support systems; Genetic algorithms; IP networks; Intrusion detection; Particle swarm optimization; Technology management; Telecommunication traffic; Particle Swarm Optimization (PSO); false alarm rate; intrusion detection; rule extraction;

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.2009.164

Filename

5231032