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A Bayesian Generalized Poisson Model for Cyber Risk Analysis

hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorRobert, Christian P.
HAL ID: 1998
ORCID: 0000-0001-6635-3261
hal.structure.identifierUniversity of Ca’ Foscari [Venice, Italy]
dc.contributor.authorCarallo, Giulia
hal.structure.identifierUniversity of Ca’ Foscari [Venice, Italy]
dc.contributor.authorCasarin, Roberto
dc.date.accessioned2022-02-25T10:55:38Z
dc.date.available2022-02-25T10:55:38Z
dc.date.issued2021
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22753
dc.language.isoenen
dc.subjectBayesian inferenceen
dc.subjectCyber risken
dc.subjectGeneralized Poissonen
dc.subject.ddc4en
dc.titleA Bayesian Generalized Poisson Model for Cyber Risk Analysisen
dc.typeChapitre d'ouvrage
dc.description.abstractenCyber threats are now considered as a top risk for many economic sectors which include retail, financial services, security, and healthcare. The costs for damages from cyber-attacks and the number of cyber-attacks are two of the main quantities of interest when measuring cyber-risk. In this paper, we focus on the frequency of cyber-attacks and analyse some features through the lens of a generalized Poisson model. We follow a Bayesian inference approach and apply a Markov Chain Monte Carlo algorithm for posterior approximation. In the application to a well-known dataset on cyber-threats we find evidence of over-dispersion and of time-variations in the features of the phenomenon.en
dc.identifier.citationpages123-128en
dc.relation.ispartoftitleMathematical and Statistical Methods for Actuarial Sciences and Financeen
dc.relation.ispartofeditorMarco Corazza, Manfred Gilli, Cira Perna, Claudio Pizzi, Marilena Sibillo
dc.relation.ispartofpublnameSpringeren
dc.relation.ispartofpublcityBerlin Heidelbergen
dc.relation.ispartofdate2021
dc.relation.ispartofurl10.1007/978-3-030-78965-7en
dc.subject.ddclabelInformatique généraleen
dc.relation.ispartofisbn978-3-030-78965-7en
dc.relation.forthcomingnonen
dc.identifier.doi10.1007/978-3-030-78965-7_19en
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2022-02-25T10:50:03Z
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