Statistical risk quantification of two-directional internet traffic flows

Piotr Kokoszka; Mengting Lin; Haonan Wang; Stephen Hayne

doi:https://doi.org/10.59170/stattrans-2024-001

Statistical risk quantification of two-directional internet traffic flows

Piotr Kokoszka Department of Statistics, Colorado State University, Fort Collins CO 80523, USA ORCID:https://orcid.org/0000-0001-9979-6536 , Mengting Lin 2Department of Statistics, Colorado State University, Fort Collins CO 80523, USA ORCID:https://orcid.org/0009-0002-7712-9585 , Haonan Wang Department of Statistics, Colorado State University, Fort Collins CO 80523, USA ORCID:https://orcid.org/0000-0002-8892-6232 , Stephen Hayne Department of Computer Information Systems, Colorado State University, Fort Collins CO 80523, USA ORCID:https://orcid.org/0000-0002-9578-3364 Statistics in Transition new series, vol. 25, 2024, 1, pages: 1-22 Published online: 6 March 2024 https://doi.org/10.59170/stattrans-2024-001 Citation: Kokoszka, P., Lin, M., Wang, H., Hayne, S., 2024. Statistical risk quantification of two-directional. Statistics in Transition new series, 25(1), pp. 1-22. https://doi.org/10.59170/stattrans-2024-001.

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ARTICLE

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ABSTRACT

We develop statistical methodology for the quantification of risk of source-destination pairs in an internet network. The methodology is developed within the framework of functional data analysis and copula modeling. It is summarized in the form of computational algorithms that use bidirectional source-destination packet counts as input. The usefulness of our approach is evaluated by an application to real internet traffic flows and via a simulation study.

KEYWORDS

Copula, Functional data, Internet traffic, Principal components, Risk quantification.

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