1. Propagation of cyber incidents in an insurance portfolio: counting processes combined with compartmental epidemiological models
- Author
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Olivier Lopez, Caroline Hillairet, Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Probabilités, Statistiques et Modélisations (LPSM (UMR_8001)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Laboratoire de Statistique Théorique et Appliquée (LSTA), and Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Statistics and Probability ,Economics and Econometrics ,emerging risks ,Computer science ,risk theory ,compartmental epidemiological models ,[QFIN.RM]Quantitative Finance [q-fin]/Risk Management [q-fin.RM] ,01 natural sciences ,010104 statistics & probability ,compartmental epi- demiological models ,Response strategy ,[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] ,0502 economics and business ,Confidence bounds ,Cyber-Insurance ,Cyber insurance ,0101 mathematics ,Event (probability theory) ,050208 finance ,05 social sciences ,Gaussian approximation ,[MATH.MATH-PR]Mathematics [math]/Probability [math.PR] ,Risk analysis (engineering) ,Cyber-attack ,Portfolio ,Statistics, Probability and Uncertainty ,Insurance portfolio ,counting processes - Abstract
In this paper, we propose a general framework to design accumulation scenarios that can be used to anticipate the impact of a massive cyber attack on an insurance portfolio. The aim is also to emphasize the role of countermeasures in stopping the spread of the attack over the portfolio, and to quantify the benefits of implementing such strategies of response. Our approach consists of separating the global dynamic of the cyber event (that can be described through compartmental epidemiological models), the effect on the portfolio, and the response strategy. This general framework allows us to obtain Gaussian approximations for the corresponding processes, and sharp confidence bounds for the losses. A detailed simulation study, which mimics the effects of a Wannacry scenario, illustrates the practical implementation of the method.
- Published
- 2020