DocumentCode :
402868
Title :
An efficient algorithm for frequent pattern in intrusion detection
Author :
Li, Qing-hua ; Jia-Jun Xiong ; Yang, Hua-bing
Author_Institution :
Coll. of Comput., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
1
fYear :
2003
fDate :
2-5 Nov. 2003
Firstpage :
138
Abstract :
In data mining-based intrusion detection system, we should make use of particular domain knowledge in relation to intrusion detection in order to efficiently extract relative rules from large amounts of audit records. This paper first gives a summary of the basic association rule algorithm and episode rule algorithm, then improves the basic algorithm considering the characteristic of audit records.
Keywords :
auditing; data mining; safety systems; association rules; audit records; data mining-based intrusion detection system; episode rule algorithm; frequent pattern; Accidents; Association rules; Computer security; Data mining; Data security; Educational institutions; Intrusion detection; Itemsets; Protection; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
Type :
conf
DOI :
10.1109/ICMLC.2003.1264458
Filename :
1264458
Link To Document :
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