Hypothesis Testing in Presence of Adversaries
Jorge González‐Ortega, David Rı́os Insua, Fabrizio Ruggeri, Refik Soyer · The American Statistician · 2019
We present an extension to the classical problem of hypothesis testing by incorporating actions of an adversary who intends to mislead the decision-maker and attain a certain benefit. After presenting the general problem within an adversarial statistical decision theory framework, we consider the cases of adversaries who can either perturb the data received or modify the underlying data-generating process parametrically. Supplemental materials for this article are available online.