Dynamic Clone Selection Algorithm Based on Genetic Algorithm for Intrusion Detection

Author

Baoyi, Wang ; Feng, Zhang

Author_Institution

Sch. of Comput. Sci. & Technol., North China Electr. Power Univ. (NCEPU), Baoding, China

Volume

1

fYear

2009

fDate

25-27 Dec. 2009

Firstpage

137

Lastpage

140

Abstract

Aimed at the problem of lower detection efficiency of detector set generated by traditional dynamic clone selection algorithm, a dynamic clone selection algorithm based on genetic algorithm is proposed. A new method of appetency calculation is introduced and the memory detector set is optimized based on genetic algorithm. An intrusion detection system based on this algorithm is designed. With KDD Cup 1999 dataset, it is proved that this algorithm achieves higher detection rate and lower missed detection rate.

Keywords

genetic algorithms; security of data; KDD Cup 1999 dataset; dynamic clone selection algorithm; genetic algorithm; intrusion detection; memory detector set; Cloning; Computational Intelligence Society; Computer applications; Computer science; Data security; Detectors; Genetic algorithms; Heuristic algorithms; Immune system; Intrusion detection; dynamic clone selection; fitness; intrusion detection; memory detector; negative selection;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on

Conference_Location

Chongqing

Print_ISBN

978-0-7695-3930-0

Electronic_ISBN

978-1-4244-5423-5

Type

conf

DOI

10.1109/IFCSTA.2009.40

Filename

5385115