Title :
Cascaded intrusion detection using an improved clustering method
Author :
Bao, Zhen ; He, Di
Author_Institution :
Dept. of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
An improved clustering method used for cascaded intrusion detection is proposed in this paper. It can detect different kinds of intrusions by arranging the processing framework in a cascaded way, based on which we can abstract corresponding features to achieve clustering. Computer simulations based on the 1999 KDD CUP dataset show the effectiveness of the proposed approach in detecting various intrusions and superiority to other clustering methods.
Keywords :
pattern clustering; security of data; KDD CUP dataset; cascaded intrusion detection; improved clustering method; Clustering methods; Computer networks; Computer security; Computer simulation; Data security; Helium; Intrusion detection; Neural networks; Support vector machines; Testing;
Conference_Titel :
Microelectronics & Electronics, 2009. PrimeAsia 2009. Asia Pacific Conference on Postgraduate Research in
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4668-1
Electronic_ISBN :
978-1-4244-4669-8
DOI :
10.1109/PRIMEASIA.2009.5397433
