Data Masking: A New Approach for Steganography?

It is well known that encryption provides secure channels for communicating entities. However, due to lack of covertness on these channels, an eavesdropper can identify encrypted streams through statistical tests and capture them for further cryptanalysis. Hence, the communicating entities can use steganography to achieve covertness. In this paper we propose a new form of multimedia steganography called data masking. Instead of embedding a secret message into a multimedia object, as in traditional multimedia steganography, we process the entire secret message to make it appear statistically similar to a multimedia object itself. Thereby we foil an eavesdropper who is primarily applying statistical tests to detect encrypted communication channels. We show that our approach can potentially give a covert channel capacity which is an order of magnitude higher than traditional steganography. Our experiments also show that steganalyzers trained with stego objects of known steganographic have a low detection accuracy for datamasked multimedia objects.