A Bayesian Generalized Poisson Model for Cyber Risk Analysis

Robert, Christian P.; Carallo, Giulia; Casarin, Roberto

Robert, Christian P.; Carallo, Giulia; Casarin, Roberto (2021), A Bayesian Generalized Poisson Model for Cyber Risk Analysis, dans Marco Corazza, Manfred Gilli, Cira Perna, Claudio Pizzi, Marilena Sibillo, Mathematical and Statistical Methods for Actuarial Sciences and Finance, Springer : Berlin Heidelberg, p. 123-128. 10.1007/978-3-030-78965-7_19

Type

Chapitre d'ouvrage

Date

2021

Titre de l'ouvrage

Mathematical and Statistical Methods for Actuarial Sciences and Finance

Auteurs de l’ouvrage

Marco Corazza, Manfred Gilli, Cira Perna, Claudio Pizzi, Marilena Sibillo

Éditeur

Springer

Ville d’édition

Berlin Heidelberg

Isbn

978-3-030-78965-7

Pages

123-128

CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Carallo, Giulia
University of Ca’ Foscari [Venice, Italy]
Casarin, Roberto
University of Ca’ Foscari [Venice, Italy]

Résumé (EN)

Cyber 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.

Mots-clés

Bayesian inference; Cyber risk; Generalized Poisson