A Probabilistic Framework for Security Scenarios with Dependent Actions

This work addresses the growing need of performing meaningful probabilistic analysis of security. We propose a framework that integrates the graphical security modeling technique of attack–defense trees with probabilistic information expressed in terms of Bayesian networks. This allows us to perform probabilistic evaluation of attack–defense scenarios involving dependent actions. To improve the efficiency of our computations, we make use of inference algorithms from Bayesian networks and encoding techniques from constraint reasoning. We discuss the algebraic theory underlying our framework and point out several generalizations which are possible thanks to the use of semiring theory

Deterrence in Cyberspace: An Interdisciplinary Review of the Empirical Literature

The popularity of the deterrence perspective across multiple scientific disciplines has sparked a lively debate regarding its relevance in influencing both offenders and targets in cyberspace. Unfortunately, due to the invisible borders between academic disciplines, most of the published literature on deterrence in cyberspace is confined within unique scientific disciplines. This chapter therefore provides an interdisciplinary review of the issue of deterrence in cyberspace. It begins with a short overview of the deterrence perspective, presenting the ongoing debates concerning the relevance of deterrence pillars in influencing cybercriminals’ and cyberattackers’ operations in cyberspace. It then reviews the existing scientific evidence assessing various aspects of deterrence in the context of several disciplines: criminology, law, information systems, and political science. This chapter ends with a few policy implications and proposed directions for future interdisciplinary academic research

Social Preferences in Decision Making Under Cybersecurity Risks and Uncertainties

The most costly cybersecurity incidents for organizations result from the failures of their third parties. This means that organizations should not only invest in their own protection and cybersecurity measures, but also pay attention to that of their business and operational partners. While economic impact and real extent of third parties cybersecurity risks is hard to quantify, decision makers inevitably compare their decisions with other entities in their network. This paper presents a theoretically derived model to analyze the impact of social preferences and other factors on the willingness to cooperate in third party ecosystems. We hypothesize that willingness to cooperate among the organizations in the context of cybersecurity increases following the experience of cybersecurity attacks and increased perceived cybersecurity risks. The effects are mediated by perceived cybersecurity value and moderated by social preferences. These hypotheses are tested using a variance-based structural equation modeling analysis based on feedback from a sample of Norwegian organizations. Our empirical results confirm the strong positive impact of social preferences and cybersecurity attack experience on the willingness to cooperate, and support the reciprocal behavior of cybersecurity decision makers. We further show that more perception of cybersecurity risk and value deter the decision makers to cooperate with other organizations