Title :
Study on Features Extracion Algorithm Based on Improved Genetic-Immune Algorithm in NIDS
Author :
Feng, Yan ; Song, Ya-nan ; Xu, Rong-hua ; Yan, Xiao-Ke
Author_Institution :
Coll. of Autom., Guangdong Univ. of Technol., Guangzhou, China
Abstract :
Features extraction in NIDS is a NP-hard problem. To improve the search speed and avoid local minimal, immune is induced into features extraction in NIDS. Similar degree and chroma are defined. Relationship based on NIDS feature code and immune operators are constructed to avoid local minimal and improve speed and quality of the found solution. Experiments are based on standard data set and use genetic algorithm, genetic-immune algorithm and improved genetic-immune algorithm. Results of experiments show that improved genetic-immune algorithm is effective.
Keywords :
computer network security; feature extraction; genetic algorithms; NIDS; NP-hard problem; feature extraction; genetic algorithm; immune operators; improved genetic immune algorithm; network intrusion detection system; Algorithm design and analysis; Clustering algorithms; Computer hacking; Feature extraction; Genetic algorithms; Immune system; Intrusion detection; NP-hard problem; Safety; Time series analysis; KDDcup99; Network intrusion detection system; features extraction; genetic algorithm; immune algorithm;
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
DOI :
10.1109/ISCID.2009.100
