Adversarial risk analysis (ARA) is a relatively new area of research that informs decision‐
making when facing intelligent opponents and uncertain outcomes. It is a decision‐theoretic …

Adversarial risk analysis has been introduced as a framework to deal with risks derived from
intentional actions of adversaries. The analysis supports one of the decisionmakers, who …

Social engineering attacks are widespread, costly, and challenging to mitigate through
technical means. Companies allocate considerable resources toward security education …

Time-series models typically assume untainted and legitimate streams of data. However, a
self-interested adversary may have incentive to corrupt this data, thereby altering a decision …

We show how adversarial risk analysis may cope with a current important security issue in
relation with piracy off the Somali coasts. Specifically, we describe how to support the owner …

Conic optimization is a significant and thriving research area within the optimization
community. Conic optimization is the general class of problems concerned with optimizing a …

This article proposes, develops, and illustrates the application of level‐k game theory to
adversarial risk analysis. Level‐k reasoning, which assumes that players play strategically …

The prevalence of security threats to organizational defense demands models that support
real-world policymaking. Security games are a potent tool in this regard; however, although …

Adversarial risk analysis is an active and important area of decision analytic research. Both
single-actor decision analysis and multiple-actor game theory have been applied to this …

Sports mega‐events, such as the Olympic Games or the Super Bowl, are attractive targets
for terrorist organizations, due to their visibility, size, and number of people involved. Two …