A study of detector generation algorithms based on artificial immune in intrusion detection system

Author

Jinyin, Chen ; Dongyong, Yang

Author_Institution

Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China

Volume

1

fYear

2011

fDate

11-13 March 2011

Firstpage

4

Lastpage

8

Abstract

Detector plays an important role in self and non-self discrimination for intrusion detection system, which makes detector generation a kernel algorithm for artificial immune system. In this paper, firstly current used binary matching rules are listed, characteristics of which are analyzed. And detector generation algorithm is divided into three main processes, including gene library, negative selection and clone selection. Evolution for gene library is explained based on the gene library theory. Several new methods are adopted to improve the performance of NSA, and finally cooperative co-evolution detector generation model is constructed which is a novel structure for intrusion detection system. This paper is aimed for researchers to focus problems on three main ideas concluded in last chapter.

Keywords

artificial immune systems; security of data; artificial immune system; binary matching rules; clone selection algorithm; cooperative coevolution detector generation model; gene library theory; intrusion detection system; kernel algorithm; negative selection algorithm; Cloning; Complexity theory; Detectors; Genetic algorithms; Immune system; Intrusion detection; Libraries; GA; artificial immune; detector generation algorithm; intrusion detection; negative selection algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Research and Development (ICCRD), 2011 3rd International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-61284-839-6

Type

conf

DOI

10.1109/ICCRD.2011.5763961

Filename

5763961