Survival Analysis and Prediction Model of IP Address Assignment Duration

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Komosný, Dan
Rehman, Saeed

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Mark

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IEEE
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Abstract

IP addresses of end hosts change when they are re-assigned. We apply survival analysis, which is commonly used in healthcare, on IP addresses to predict their assignment duration (their lifetime). We propose a survival parametric model based on a history of 6 years of address assignments on a worldwide scale. Our model outperforms alternative models both from short-term and long-term views. The custom modelling is also discussed as address assignment varies across Internet service providers (ISPs) and autonomous systems (ASs). A predictable address assignment duration has many applications, including source reputation, topology mapping, and geolocation. We describe a use-case in fraud prevention, where the proposed model is used as a trigger for two-factor authentication. The created dataset of addresses assignment durations is made publicly available.
IP addresses of end hosts change when they are re-assigned. We apply survival analysis, which is commonly used in healthcare, on IP addresses to predict their assignment duration (their lifetime). We propose a survival parametric model based on a history of 6 years of address assignments on a worldwide scale. Our model outperforms alternative models both from short-term and long-term views. The custom modelling is also discussed as address assignment varies across Internet service providers (ISPs) and autonomous systems (ASs). A predictable address assignment duration has many applications, including source reputation, topology mapping, and geolocation. We describe a use-case in fraud prevention, where the proposed model is used as a trigger for two-factor authentication. The created dataset of addresses assignment durations is made publicly available.

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IEEE Access. 2020, vol. 8, issue 1, p. 162507-162515.
https://ieeexplore.ieee.org/document/9186701

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Peer-reviewed

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en

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Except where otherwised noted, this item's license is described as Creative Commons Attribution 4.0 International
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