DocumentCode
518873
Title
An improved artificial immune approach to network intrusion detection
Author
Fang, Xianjin ; Li, Longshu
Author_Institution
Sch. of Comput. Sci. & Eng., Anhui Univ. of Sci. & Technol., Huainan, China
Volume
2
fYear
2010
fDate
27-29 March 2010
Firstpage
39
Lastpage
44
Abstract
The definition of vaccine, vaccine autonomous obtaining algorithm, vaccination operator and evolution of vaccine library are proposed in this paper. The generic clonal selection algorithm is improved by integrating with vaccine autonomous obtaining and vaccination operator, whose purpose is to accelerate the convergence speed of clonal selection algorithm, and improve the efficiency of the algorithm. The improved clonal selection algorithm together with negative selection mechanism in immunology is used to create the model of network intrusion detection. Simulated experimental results and theoretical computation efficiency analyses demonstrate the availability of the model and the speedup of convergence.
Keywords
artificial immune systems; computer network security; artificial immune approach; computation efficiency; convergence speed; generic clonal selection algorithm; immunology; negative selection mechanism; network intrusion detection; vaccination operator; vaccine autonomous obtaining algorithm; vaccine library evolution; Acceleration; Analytical models; Computational modeling; Computer science; Detectors; Genetic mutations; Immune system; Intrusion detection; Libraries; Vaccines; Artificial Immune System; Clonal Selection Algorithm; Vaccination operator; network Intrusion Detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location
Shenyang
Print_ISBN
978-1-4244-5845-5
Type
conf
DOI
10.1109/ICACC.2010.5487176
Filename
5487176
Link To Document