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.

Volume

2

fYear

2004

fDate

2004

Firstpage

873

Lastpage

878

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics and Intelligent Systems, 2004 IEEE Conference on

Conference_Location

Singapore

Print_ISBN

0-7803-8643-4

Type

conf

DOI

10.1109/ICCIS.2004.1460703

Filename

1460703