Title :
Design of mnitiple-level tree classifiers for intrusion detection system
Author :
Xiang, C. ; Chong, M.Y. ; Zhu, H.L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Singapore Nat. Univ.
Abstract :
Intrusion detection system (IDS) has recently emerged as an important component for enhancing information system security. To effectively build corresponding rules and patterns of computer attack scenarios and system vulnerabilities, data mining has been widely used in constructing and maintaining IDS. Based on statistical characteristics of specific intrusion types, a novel approach of using multiple-level tree classifiers is proposed in this paper to identify intrusions. Performance of this new algorithm is compared to other popular approaches such as MADAM ID (Lee and Stolfo, 2000)
Keywords :
data mining; pattern classification; security of data; telecommunication security; tree searching; computer attack scenario; data mining; information system security; intrusion detection system; intrusion identification; multiple-level tree classifier; system vulnerability; Algorithm design and analysis; Classification algorithms; Classification tree analysis; Computer networks; Computer security; Computerized monitoring; Data mining; Databases; Decision trees; Intrusion detection;
Conference_Titel :
Cybernetics and Intelligent Systems, 2004 IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
0-7803-8643-4
DOI :
10.1109/ICCIS.2004.1460703
