Neural Networks for Artificial Immune Systems: LVQ for Detectors Construction

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Bezobrazov, S.  Golovko, V. 
Brest State Tech. Univ., Brest 

This paper appears in: Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2007. IDAACS 2007. 4th IEEE Workshop on
Publication Date: 6-8 Sept. 2007
On page(s): 180 - 184
Location: Dortmund
Print ISBN: 978-1-4244-1347-8
INSPEC Accession Number: 9905358
Digital Object Identifier: 10.1109/IDAACS.2007.4488401
Date of Current Version: 15 4月 2008

Abstract

This paper presents a non-standard approach for solving computer viruses detection problem based on the artificial immune system (AIS) method. The AIS is the biologically-inspired technique which have powerful information processing capabilities that makes it attractive for applying in computer security systems. Computer security systems based on AIS principles allow detect unknown malicious code. In this work we are describing model build on the AIS approach in which detectors represent the learning vector quantization (LVQ) neural networks. Basic principles of the biological immune system and comparative analysis of unknown computer viruses detection for different antivirus software and our model are presented.

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