A dynamic artificial immune-based intrusion detection method using rough and fuzzy set

Author

Ling Zhang ; Zhongying Bai ; Shoushan Luo ; Guanning Cui ; Xing Li

Author_Institution

Sch. of Comput. Sci., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2013

fDate

22-24 Nov. 2013

Firstpage

1

Lastpage

7

Abstract

Artificial immune is proven to be an effective method for adaptive intrusion detection. By using rough set (RS) and fuzzy set (FS), a dynamic artificial immune-based intrusion detection method using rough and fuzzy set is designed (DAIIDRF). A scheme based on rough set for antibodies is proposed. Using antibodies obtainment method, excellent antibodies are promised, at the same time, the detection speed is improved, the convergence rate is higher. At last, the simulation experiments with KDD99 and the comparisons of two algorithms are given. The experimental results show its feasibility and effectiveness of the proposed method.

Keywords

artificial immune systems; fuzzy set theory; rough set theory; security of data; DAIIDRF; KDD99; adaptive intrusion detection; antibodies obtainment method; dynamic artificial immune-based intrusion detection method; fuzzy set; rough set; Artificial immune; Fuzzy set; Intrusion detection; Rough set;

fLanguage

English

Publisher

iet

Conference_Titel

Information and Network Security (ICINS 2013), 2013 International Conference on

Conference_Location

Beijing

Electronic_ISBN

978-1-84919-729-8

Type

conf

DOI

10.1049/cp.2013.2458

Filename

6826007