The Steganographer is the Outlier: Realistic Large-Scale Steganalysis

We present a method for a completely new kind of steganalysis to determine who, out of a large number of actors each transmitting a large number of objects, is hiding payload inside some of them. It has significant challenges, including unknown embedding parameters and natural deviation between innocent cover sources, which are usually avoided in steganalysis tested under laboratory conditions. Our method uses standard steganalysis features, the maximum mean discrepancy measure of distance, and ranks the actors by their degree of deviation from the rest: we show that it works reliably, completely unsupervised, when tested against some of the standard steganography methods available to nonexperts. We also determine good parameters for the detector and show that it creates a two-player game between the guilty actor and the steganalyst.