The Square Root Law of Steganography: Empirical Validation
AbstractSteganography means hiding a hidden payload within an apparently-innocent cover, usually an item of digital media (in this project: images). Steganalysis is the art of detecting that hiding took place. A key question is how the amount of information that can be securely hidden (i.e. such that detectors have a high error rate) scales with the size of the cover. In 2008 I co-authored a paper showing that my theoretical "square root law" was observed experimentally, using state-of-the-art (for 2008) hiding and detection methods. This project is to run similar experiments using methods 10 years more modern. It would involve combining off-the-shelf code (some in MATLAB, some in Python) from various researchers and running fairly large scale experiments to measure detection accuracy versus cover size and payload size in tens of thousands of images, then graphing the results suitably.
Prerequisites: No particular prerequisites. Ability to piece together others' code and draw graphs nicely.