  Adversarial optimal transport has been proven useful as a mathematical
formulation to model resource allocation problems to maximize the efficiency of
transportation with an adversary, who modifies the data. It is often the case,
however, that only the adversary knows which nodes are malicious and which are
not. In this paper we formulate the problem of seeking adversarial optimal
transport into Bayesian games. We construct the concept of Bayesian equilibrium
and design a distributed algorithm that achieve those equilibria, making our
model applicable to large-scale networks. Keywords: game theory, crime control,
Markov games
