My current research focus is the application of Machine Learning and Deep Learning in Steganography and Steganalysis.
Steganography is the art of covert communication when secrets are hidden in ordinary looking cover objects. The goal is to make steganographic communication indistinguishable from regular exchange of information during which no secrets are passed between communicating parties.
Digital media, such as images, are particularly suitable cover objects because of their ubiquity and because they can be slightly modified without changing their appearance, potentially thus able to hold large messages. The task of detecting the presence of steganography is complicated by the fact that images contain many indeterministic components due to the acquisition conditions and to the high diversity and complexity introduced during development from the raw capture, post-processing, editing, and even sharing.
The steganography/steganalysis problem is often described by the prisoners’ problem, Alice and Bob are allowed to communicate but all messages they exchange are closely monitored by warden Eve looking for potential hidden data in their communication.