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Introductions to Adversary Behavior: Validating the Models

This special issue discusses the validation of models of adversary behavior, which was studied at the First Conference on Validating Models of Adversary Behavior, organized by Dr. Jun Zhuang and Dr. Vicki Bier in Buffalo/Niagara Falls, NY, June 23–26, 2013. This issue contains some selected papers from that conference, and also additional contributions. Validation is critical for models that are intended to be used in practice, and is required by some organizations that wish to use models of adversary behavior. Various models have been proposed in the literature to better understand intelligent-adversary behavior, and the strategic interactions between defenders and intelligent adversaries (such as terrorists or other attackers). However, few if any such models have been validated to date because of the sparsity of empirical data, which limits the applicability of the models in practice. In homeland security, defenders make decisions about allocating limited resources to prevent, prepare, and respond to attacks from adversaries. The purpose of intelligent-adversary risk assessment is to deter or mitigate the effects of adversary attacks by making it possible to allocate limited defensive resources more efficiently. When decisionmakers apply a model to predict adversaries’ behavior and allocate resources accordingly, they would like to have confidence that the model adequately represents the real situation, including the strategy choices and level of rationality of the adversaries. It is obviously challenging to assess the likelihood that an attack will be launched at a particular time or place, or even using a particular strategy. Moreover,