A Bayesian Generalized Poisson Model for Cyber Risk Analysis

Giulia Carallo (), Roberto Casarin and Christian P. Robert ()
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Giulia Carallo: University Ca’ Foscari
Christian P. Robert: University Paris Dauphine

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2021, pp 123-128 from Springer

Abstract: Abstract 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.

Keywords: Bayesian inference; Cyber risk; Generalized Poisson (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-78965-7_19

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DOI: 10.1007/978-3-030-78965-7_19

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