TRIST: Circumventing Censorship with Transcoding-Resistant Image Steganography

We explore the viability of extending state-of-the-art image steganography techniques for bypassing censorship. Our quest for a scalable steganographic technique, which is robust against automated transcoders that reformat images in-flight, led to the implementation of a prototype system called TRIST that embeds data by selectively modifying bits in the frequency domain of the image. By choosing heavily quantized frequency components at low JPEG quality values, we can robustly embed information within images, and demonstrate how this information survives a number of transformations, including transcoding to higher JPEG quality levels and other perturbations, such as image resizing (within bounds).

We evaluate our system by building a prototype of a transcoding-resistant steganography library that we integrate with StegoTorus. Our evaluations demonstrate that StegoTorus integrated with TRIST provides reasonable bandwidth capable of supporting basic web surfing along with transcoding resilience. Finally, we describe how our system can be adapted to counter state-of-theart statistical attacks such as blockiness detectors.