Intrusion Detection Using Evolutionary Neural Networks

Author

Michailidis, Emmanuel ; Katsikas, Sokratis K. ; Georgopoul, Efstratios

Author_Institution

Dept. of Technol. Educ. & Digital Syst., Piraeus Univ., Piraeus

fYear

2008

fDate

28-30 Aug. 2008

Firstpage

8

Lastpage

12

Abstract

In this paper a network intrusion detection system using evolutionary neural networks (ENN´s) is proposed. The analysis engine of the IDS is modeled by the ENN and its ability to predict attacks in a network environment is evaluated. The ENN is trained by a particle swarm optimization (PSO) algorithm using labeled data from the KDD cup ´99 competition.The results from the experiments are compared to the results bythe same competition and give positive results in the recognitionof DoS and probe attacks.

Keywords

neural nets; particle swarm optimisation; security of data; DoS attacks; ENN; IDS; KDD cup 99 competition; PSO; evolutionary neural networks; network intrusion detection system; particle swarm optimization algorithm; Algorithm design and analysis; Computer networks; Engines; Informatics; Intrusion detection; Neural networks; Particle swarm optimization; Predictive models; Probes; Software systems; ENN; Evolutionary Neural Networks; Intrusion Detection; Misuse Detection; Particle Swarm Optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Informatics, 2008. PCI '08. Panhellenic Conference on

Conference_Location

Samos

Print_ISBN

978-0-7695-3323-0

Type

conf

DOI

10.1109/PCI.2008.53

Filename

4621529