Survival Analysis and Prediction Model of IP Address Assignment Duration

dc.contributor.authorKomosný, Dancs
dc.contributor.authorRehman, Saeedcs
dc.coverage.issue1cs
dc.coverage.volume8cs
dc.date.issued2020-09-04cs
dc.description.abstractIP 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.en
dc.description.abstractIP 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.en
dc.formattextcs
dc.format.extent162507-162515cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationIEEE Access. 2020, vol. 8, issue 1, p. 162507-162515.en
dc.identifier.doi10.1109/ACCESS.2020.3021760cs
dc.identifier.issn2169-3536cs
dc.identifier.orcid0000-0002-6551-7997cs
dc.identifier.other164961cs
dc.identifier.urihttp://hdl.handle.net/11012/195582
dc.language.isoencs
dc.publisherIEEEcs
dc.relation.ispartofIEEE Accesscs
dc.relation.urihttps://ieeexplore.ieee.org/document/9186701cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2169-3536/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectIP addressen
dc.subjectsurvivalen
dc.subjectlifetimeen
dc.subjecthosten
dc.subjectassignmenten
dc.subjectsecurityen
dc.subjectIPv4en
dc.subjectIPv6en
dc.subjectIP address
dc.subjectsurvival
dc.subjectlifetime
dc.subjecthost
dc.subjectassignment
dc.subjectsecurity
dc.subjectIPv4
dc.subjectIPv6
dc.titleSurvival Analysis and Prediction Model of IP Address Assignment Durationen
dc.title.alternativeSurvival Analysis and Prediction Model of IP Address Assignment Durationen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-164961en
sync.item.dbtypeVAVen
sync.item.insts2025.10.14 14:12:04en
sync.item.modts2025.10.14 10:10:57en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs

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