Intrusion detection using data mining techniques

Author

Ektefa, Mohammadreza ; Memar, Sara ; Sidi, Fatimah ; Affendey, Lilly Suriani

Author_Institution

Dept. of IS, UPM, Serdang, Malaysia

fYear

2010

fDate

17-18 March 2010

Firstpage

200

Lastpage

203

Abstract

As the network dramatically extended, security considered as major issue in networks. Internet attacks are increasing, and there have been various attack methods, consequently. Intrusion detection systems have been used along with the data mining techniques to detect intrusions. In this work we aim to use data mining techniques including classification tree and support vector machines for intrusion detection. As results indicate, C4.5 algorithm is better than SVM in detecting network intrusions and false alarm rate in KDD CUP 99 dataset.

Keywords

data mining; security of data; support vector machines; C4.5 algorithm; Internet attacks; data mining; intrusion detection; support vector machines; Application software; Classification tree analysis; Data mining; Data security; IP networks; Internet; Intrusion detection; Support vector machine classification; Support vector machines; Telecommunication traffic; Classification tree; Data Mining; Internet attack; Intrusion Detection Systems (IDS); Support Vector Machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Retrieval & Knowledge Management, (CAMP), 2010 International Conference on

Conference_Location

Shah Alam, Selangor

Print_ISBN

978-1-4244-5650-5

Type

conf

DOI

10.1109/INFRKM.2010.5466919

Filename

5466919