Title
Evaluating Sequential Combination of Two Genetic Algorithm-Based Solutions for Intrusion Detection.
Abstract
The paper presents a serial combination of two genetic algorithm-based intrusion detection systems. Feature extraction techniques are deployed in order to reduce the amount of data that the system needs to process. The designed system is simple enough not to introduce significant computational overhead, but at the same time is accurate, adaptive and fast. There is a large number of existing solutions based on machine learning techniques, but most of then) introduce high computational overhead. Moreover, due to its inherent parallelism, our solution offers a possibility of implementation using reconfigurable hardware with the implementation cost much lower than the one of the traditional systems. The model is verified on KDD99 benchmark dataset, generating a solution competitive with the solutions of the state-of-the-art.
Year
DOI
Venue
2008
10.1007/978-3-540-88181-0_19
PROCEEDINGS OF THE INTERNATIONAL WORKSHOP ON COMPUTATIONAL INTELLIGENCE IN SECURITY FOR INFORMATION SYSTEMS CISIS 2008
Keywords
Field
DocType
intrusion detection,genetic algorithm,sequential combination,principal component analysis,multi expression programming
Overhead (computing),Computer science,Real-time computing,Feature extraction,Multi expression programming,Computer engineering,Intrusion detection system,Principal component analysis,Genetic algorithm,Reconfigurable computing
Conference
Volume
ISSN
Citations 
53
1615-3871
1
PageRank 
References 
Authors
0.37
7
3
Name
Order
Citations
PageRank
Zorana Banković111216.91
Slobodan Bojanic2727.91
Octavio Nieto-Taladriz317318.15