Anomaly detection based on GA&FART approach of computer network security
Date
2012
ISBN
978-088986911-0
Journal Title
Journal ISSN
Volume Title
Resource Type
Conference paper
Publisher
Journal Title
Anomaly detection based on GA&FART approach of computer network security
Recommended by
Abstract
The problems of intrusion detection in a computer network security are difficulty of having a protective line in the information security against attackers. Researchers have developed Intrusion Detection System (IDS) which is capable of detecting attacks in several available environments. This paper aims to provide the intrusion detection technique into the system by using integrates like the Genetic Algorithm (GA) with the Fuzzy Adaptive Resonance Theory (FART). The GA is applied to randomly select the best attribution and reduction to the featured space. The FART is used to classify different group of data: Normal and Anomalous. The results show that this proposed technique can improve the performance of anomalous detection, showing the high performance of the detection rate and minimizing the false alarm rate. The approach was evaluated on the benchmark data from KDDCup'99 data set.
Description
Citation
Proceedings of the 2nd IASTED Asian Conference on Modelling, Identification, and Control, AsiaMIC 2012