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 :
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