Title :
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
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;
Conference_Titel :
Informatics, 2008. PCI '08. Panhellenic Conference on
Conference_Location :
Samos
Print_ISBN :
978-0-7695-3323-0
DOI :
10.1109/PCI.2008.53
