Bayesian mechanisms for wireless network security

Strategic users in a wireless network cannot be assumed to follow the network algorithms blindly. Moreover, some of these users could be controlled by powerful Botnets, which aim to use their knowledge about network algorithms to maliciously gain more resources and also to create interference to other users. We consider a scenario; in which a mechanism designer and legitimate users together, in a wireless network, gather probabilistic information about the presence of malicious users and modify their actions accordingly. The probabilistic information is gathered by observing the network over a long time period. We study Bayesian mechanisms, both pricing schemes and auctions, and obtain the Nash Equilibrium (NE) points of the underlying Bayesian games. The NE points provide conditions indicating when it is better for users to to hide or reveal their nature (types). The prices and allocations in the mechanisms are later modified using the Bayesian information about the type of the users. The numerical studies show the NE points and illustrate the results.