Neural Networks for Artificial Immune Systems: LVQ for Detectors Construction

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.

[1]  Martin T. Hagan,et al.  Neural network design , 1995 .

[2]  Alan S. Perelson,et al.  Self-nonself discrimination in a computer , 1994, Proceedings of 1994 IEEE Computer Society Symposium on Research in Security and Privacy.

[3]  Stephanie Forrest,et al.  Coverage and Generalization in an Artificial Immune System , 2002, GECCO.

[4]  Zbigniew Michalewicz,et al.  Genetic algorithms + data structures = evolution programs (3rd ed.) , 1996 .

[5]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[6]  Martín Abadi,et al.  Theoretical Aspects of Computer Software , 1991, Lecture Notes in Computer Science.

[7]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1992, Artificial Intelligence.

[8]  C. Janeway How the immune system recognizes invaders. , 1993, Scientific American.

[9]  Stephanie Forrest,et al.  Architecture for an Artificial Immune System , 2000, Evolutionary Computation.

[10]  Sun-Yuan Kung,et al.  Biometric Authentication: A Machine Learning Approach , 2004 .

[11]  Jonathan Timmis,et al.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[12]  N. K. Jerne,et al.  Clonal selection in a lymphocyte network. , 1974, Society of General Physiologists series.