Publication: Applying multivariate data analysis to identify key parameters of bi-directional attack flows
Issued Date
2015-01-01
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2-s2.0-84938150855
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Mahidol University
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SCOPUS
Bibliographic Citation
ACDT 2015 - Proceedings: The 1st Asian Conference on Defence Technology. (2015)
Suggested Citation
Korakoch Wilailux, Sudsanguan Ngamsuriyaroj Applying multivariate data analysis to identify key parameters of bi-directional attack flows. ACDT 2015 - Proceedings: The 1st Asian Conference on Defence Technology. (2015). doi:10.1109/ACDT.2015.7111611 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/35823
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Title
Applying multivariate data analysis to identify key parameters of bi-directional attack flows
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Abstract
© 2015 IEEE. Flow export data has been intensively used in anomaly-based intrusion detection systems; however, we have limited understanding of the characteristics of bi-directional flow parameters with respect to the types of network attacks. To recognize the relationship between traffic parameters, we propose an empirical model which analyzes synthetically generated five network attacks within a closed environment, and perform exploratory data analysis using principal component analysis. The experimental results have identified relevant key parameters for selecting good candidates for intrusion detection analysis. The analysis capabilities of bi-directional flow parameters and their characteristics persisting in selected attacks have been diagnosed and revealed.