Framework for Cyber Risk Loss Distribution of Client-Server Networks: A Bond Percolation Model and Industry Specific Case Studies

40 Pages Posted: 16 Jun 2022

See all articles by Stefano Chiaradonna

Stefano Chiaradonna

Arizona State University (ASU)

Petar Jevtic

Arizona State University (ASU) - School of Mathematical and Statistical Sciences

Nicolas Lanchier

Arizona State University (ASU)

Sasa Pesic

Arizona State University (ASU)

Date Written: May 16, 2022

Abstract

Cyber risk has emerged as a significant threat to businesses that have increasingly relied on new and existing information technologies (IT). Across various businesses in different industries and sectors, a distinct pattern of IT network architectures, such as the client-server network architecture, may, in principle, expose those businesses, which share it, to similar cyber risks. That is why in this paper, we propose a probabilistic structural framework for loss assessments of cyber risks on the class of client-server network architectures with K different client types. Up to our knowledge, there exist no theoretical models of an aggregate loss distribution for cyber risk in this setting. With this structural framework via the exact mean and variance of losses, we demonstrate how a changing cybersecurity environment of a business's IT network impacts the loss distribution. Further, our framework provides insights into better investment strategies for cybersecurity protection on the client-server network. Motivated by cyberattacks across industries, we apply our framework to four case studies that utilize the client-server network architecture. Our first application is implantable medical devices in healthcare. Our second application is the smart buildings domain. Third, we present an application for ride-sharing services such as Uber and Lyft. The fourth is the application of vehicle-to-vehicle cooperation in traffic management. The results are corresponding exact means and variances of cyber risk loss distributions parameterized by various cybersecurity parameters allowing for liability assessments and decisions in cybersecurity protection investments.

Keywords: Cyber Risk, Bond Percolation, Client-Server, Smart Buildings, Ride-Sharing, Implantable Medical Devices, Vehicle-to-Vehicle Cooperation

Suggested Citation

Chiaradonna, Stefano and Jevtic, Petar and Lanchier, Nicolas and Pesic, Sasa, Framework for Cyber Risk Loss Distribution of Client-Server Networks: A Bond Percolation Model and Industry Specific Case Studies (May 16, 2022). Available at SSRN: https://ssrn.com/abstract=4129369 or http://dx.doi.org/10.2139/ssrn.4129369

Stefano Chiaradonna (Contact Author)

Arizona State University (ASU) ( email )

900 S Palm Walk
Tempe, AZ 85287
United States

Petar Jevtic

Arizona State University (ASU) - School of Mathematical and Statistical Sciences ( email )

900 S Palm Walk
Tempe, AZ 85287-1804
United States

HOME PAGE: http://https://math.asu.edu/node/2745

Nicolas Lanchier

Arizona State University (ASU) ( email )

Sasa Pesic

Arizona State University (ASU) ( email )

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