DocumentCode
589258
Title
An Artificial Immune System Based on Holland´s Classifier as Network Intrusion Detection
Author
Randrianasolo, Arisoa S. ; Pyeatt, Larry D.
Author_Institution
Sch. of Comput. & Inf., Lipscomb Univ., Nashville, TN, USA
Volume
1
fYear
2012
fDate
12-15 Dec. 2012
Firstpage
504
Lastpage
507
Abstract
In this paper, an Artificial Immune System based on Hollandâs Classifier is proposed as a new method for network intrusion detection. This paper is not aimed to provide a comparative study but to give more understanding on the feasibility of combining Artificial Immune System and Hollandâs Classifier to detect network intrusion. This new Artificial Immune System, named AIS-CS, can attain higher than 90% intrusion detection with a false negative percentage below 10% and a fairly low false positive rate on a network composed of 50 regular nodes and 50 intruders. The experiments appear to suggest that the best performance can be found by setting the tolerization and the simulation parameters differently. Since there are numerous parameters involved, more experiments need to be performed to further measure this Holland classifier based Artificial Immune System.
Keywords
artificial immune systems; computer network security; pattern classification; AIS-CS; Holland classifier; artificial immune system; false negative; false positive rate; intruders; network intrusion detection; regular nodes; simulation parameters; Biological information theory; Computers; Detectors; Genetic algorithms; Immune system; Intrusion detection; USA Councils; Artificial Immune System; Holland´s Classifier; Intrusion Detection System;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications (ICMLA), 2012 11th International Conference on
Conference_Location
Boca Raton, FL
Print_ISBN
978-1-4673-4651-1
Type
conf
DOI
10.1109/ICMLA.2012.92
Filename
6406663
Link To Document