Related papers: Pricing cyber-insurance for systems via maturity m…

In this paper we consider pricing of insurance contracts for breast cancer risk based on three multiple state models. Using population data in England and data from the medical literature, we calibrate a collection of semi-Markov and Markov…

Digitization increases business opportunities and the risk of companies being victims of devastating cyberattacks. Therefore, managing risk exposure and cybersecurity strategies is essential for digitized companies that want to survive in…

As insurers increasingly behave like financial intermediaries and actively participate in capital markets, understanding the dependence structure between insurance and financial risks becomes crucial for insurers' operations. This paper…

Cybersecurity risk analysis plays an essential role in supporting organizations make effective decision about how to manage and control cybersecurity risk. Cybersecurity risk is a function of the interplay between the defender, i.e., the…

Supply chain security threats pose new challenges to security risk modeling techniques for complex ICT systems such as the IoT. With established techniques drawn from attack trees and reliability analysis providing needed points of…

In Industry 4.0, Cyber-Physical Systems (CPS) are formed by components, which are interconnected with each other over the Internet of Things (IoT). The resulting capabilities of sensing and affecting the physical world offer a vast range of…

This paper is devoted to measuring the security of cyber networks under advanced persistent threats (APTs). First, an APT-based cyber attack-defense process is modeled as an individual-level dynamical system. Second, the dynamic model is…

Data are invaluable. How can we assess the value of data objectively, systematically and quantitatively? Pricing data, or information goods in general, has been studied and practiced in dispersed areas and principles, such as economics,…

In this work we start walking the path to a new perspective for viewing cyberwarfare scenarios, by introducing conceptual tools (a formal model) to evaluate the costs of an attack, to describe the theater of operations, targets, missions,…

The ability to accurately predict cyber-attacks would enable organizations to mitigate their growing threat and avert the financial losses and disruptions they cause. But how predictable are cyber-attacks? Researchers have attempted to…

This paper addresses significant obstacles that arise from the widespread use of machine learning models in the insurance industry, with a specific focus on promoting fairness. The initial challenge lies in effectively leveraging unlabeled…

Cybersecurity risk is commonly expressed through impact and likelihood, yet likelihood remains difficult to estimate because cyber incidents are underreported, heterogeneous datasets are weakly comparable, and attacker behaviour changes…

Cyber-security breaches inflict significant costs on organizations. Hence, the development of an information-systems defense capability through cyber-security investment is a prerequisite. The question of how to determine the optimal amount…

As new technologies such as the Internet of Things (IoT) are integrated into Critical National Infrastructures (CNI), new cybersecurity threats emerge that require specific security solutions. Approaches used for analysis include the…

Cloud computing is revolutionising the way software services are procured and used by Government organizations and SMEs. Quantitative risk assessment of Cloud services is complex and undermined by specific security concerns regarding data…

Due to the complex nature of mobile communication systems, most of the security efforts in its domain are isolated and scattered across underlying technologies. This has resulted in an obscure view of the overall security. In this work, we…

Cloud computing is a new computational paradigm that offers an innovative business model for organizations to adopt IT without upfront investment. Despite the potential gains achieved from the cloud computing, the model security is still…

Major transformations related to information technologies affect InformationSystems (IS) that support the business processes of organizations and their actors. Deployment in a complex environment involving sensitive, massive and…

Machine learning is disruptive. At the same time, machine learning can only succeed by collaboration among many parties in multiple steps naturally as pipelines in an eco-system, such as collecting data for possible machine learning…

Machine Learning permeates many industries, which brings new source of benefits for companies. However within the life insurance industry, Machine Learning is not widely used in practice as over the past years statistical models have shown…