DocumentCode
1634174
Title
An intrusion detection method based on rough set and SVM algorithm
Author
Hong, Peng ; Zhang, Dongna ; Wu, Tiefeng
Author_Institution
Sch. of Comput. & Math.-Phys. Sci., Xihua Univ., Chengdu, China
Volume
2
fYear
2004
Firstpage
1127
Abstract
This paper proposes an intrusion detection method that combines rough sets and SVM algorithm. By virtue of the ability rough sets have to decrease the amount of data and get rid of redundancy, the method can reduce the amount of training data and overcome the SVM defect of slow running speed when processing large datasets. At the same time, by the aid of the SVM algorithm the method can classify the core of the property set to have extensiveness and high identification rate, and avoid disturbances. Experimental results show this method is better than other methods reported in the literature in terms of detection resolution.
Keywords
authorisation; computer network management; data reduction; rough set theory; support vector machines; SVM algorithm; data reduction; identification rate; intrusion detection method; rough sets; Computer networks; Computer security; Data security; Intrusion detection; Learning systems; Machine learning algorithms; Redundancy; Support vector machine classification; Support vector machines; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Circuits and Systems, 2004. ICCCAS 2004. 2004 International Conference on
Print_ISBN
0-7803-8647-7
Type
conf
DOI
10.1109/ICCCAS.2004.1346374
Filename
1346374
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