Game‐theoretic computing in risk analysis

Abstract

AbstractRisk analysis, comprising risk assessment and risk management stages, is one of the most popular and challenging topics of our times because security and privacy, and availability and usability culminating at the trustworthiness of cybersystems and cyber information is at stake. The precautionary need derives from the existence of defenders versus adversaries, in an everlasting Darwinian scenario dating back to early human history of warriors fighting for their sustenance to survive. Fast forwarding to today's information warfare, whether in networks or healthcare or national security, the currently dire situation necessitates more than a hand calculator to optimize (maximize gains or minimize losses) risk due to prevailing scarce economic resources. This article reviews the previous works completed on this specialized topic of game‐theoretic computing, its methods and applications toward the purpose of quantitative risk assessment and cost‐optimal management in many diverse disciplines including entire range of informatics‐related topics. Additionally, this review considers certain game‐theoretic topics in depth historically, and those computationally resourceful such as Neumann's two‐way zero‐sum pure equilibrium and optimal mixed strategy solutions versus Nash equilibria with pure and mixed strategies. Computational examples are provided to highlight the significance of game‐theoretic solutions used in risk assessment and management, particularly in reference to cybersystems and information security. WIREs Comput Stat 2012, 4:227–248. doi: 10.1002/wics.1205This article is categorized under: Algorithms and Computational Methods > Linear Programming Algorithms and Computational Methods > Networks and Security