An Adversarial Risk Analysis Framework for Batch Acceptance Problems

We provide an adversarial risk analysis framework for batch acceptance problems in which a decision maker relies exclusively on the size of to accept or reject its admission system, albeit being aware presence opponent. The adversary acts as data-fiddler attacker perturbing observations perceived by through injecting faulty items and/or modifying existing ones. develop optimal policies against this combined attack strategy and illustrate methodology with review spam example.