Title :
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
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;
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
DOI :
10.1109/IFCSTA.2009.40
