e-ISSN:0976-5166
p-ISSN:2231-3850


INDIAN JOURNAL OF COMPUTER SCIENCE AND ENGINEERING

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ABSTRACT

Title : Adaptive Genetic Algorithm Model for Intrusion Detection
Authors : K. S. Anil Kumar, Dr. V. Nanda Mohan
Keywords : Intrusion Detection System (IDS), K-Means Clustering, Neuro - Genetic, DARPA dataset
Issue Date : Aug-Sep 2012
Abstract :
Intrusion detection systems are intelligent systems designed to identify and prevent the misuse of computer networks and systems. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Thus the emerging network security systems need be part of the life system and this is possible only by embedding knowledge into the network. The Adaptive Genetic Algorithm Model - IDS comprising of K-Means clustering Algorithm, Genetic Algorithm and Neural Network techniques. The technique is tested using multitude of background knowledge sets in DARPA network traffic datasets.
Page(s) : 595-599
ISSN : 0976-5166
Source : Vol. 3, No.4