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Proceedings Paper

Association rule mining in intrusion detection systems
Author(s): Dong Zhao; Yan-sheng Lu
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Paper Abstract

In a modern computer system, intrusion detection has become an essential and critical component. Data mining generally refers to the process of extracting models from large stores of data. The intrusion detection system first apply data mining programs to audit data to compute frequent patterns, extract features, and then use classification algorithms to compute detection models. The most important step of this process is to determine relations between fields in the database records to construct features. The standard association rules have not enough expressiveness. Intrusion detection system can extract the association rule with negations and with varying support thresholds to get better performance rather than extract the standard association rule.

Paper Details

Date Published: 15 April 2004
PDF: 5 pages
Proc. SPIE 5282, Network Architectures, Management, and Applications, (15 April 2004); doi: 10.1117/12.518822
Show Author Affiliations
Dong Zhao, Huazhong Univ. of Science and Technology (China)
Yan-sheng Lu, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 5282:
Network Architectures, Management, and Applications
S. J. Ben Yoo; Kwok-wai Cheung; Yun-Chur Chung; Guangcheng Li, Editor(s)

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