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.
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Carallo, G., Casarin, R., Robert, C.P. (2021). A Bayesian Generalized Poisson Model for Cyber Risk Analysis. In: Corazza, M., Gilli, M., Perna, C., Pizzi, C., Sibillo, M. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham. https://doi.org/10.1007/978-3-030-78965-7_19
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DOI: https://doi.org/10.1007/978-3-030-78965-7_19
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Online ISBN: 978-3-030-78965-7
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