Secure Payload Scaling in Detector-Informed Batch Steganography: The Mismatched Detectors Case

This paper deals with the problem of batch steganography and pooled steganalysis when the sender uses a steganography detector to spread chunks of the payload across a bag of cover images while the Warden uses a possibly different detector for her pooled steganalysis.We investigate how much information can be communicated with increasing bag size at a fixed statistical detectability of Warden's detector.Specifically, we are interested in the scaling exponent of the secure payload () = .We approach this problem both theoretically from a statistical model of the soft output of a detector and practically using experiments on real datasets when giving both actors different detectors implemented as convolutional neural networks and a classifier with a rich model.While the effect of the detector mismatch depends on the payload allocation algorithm and the type of mismatch, in general the mismatch decreases the constant of proportionality as well as the exponent .This stays true independently of who has the superior detector.Many trends observed in experiments qualitatively match the theoretical predictions derived within our model.Finally, we summarize our most important findings as lessons for the sender and for the Warden.