> Information theoretically speaking, how do you generate a "synthetic" dataset (as the article calls it) with the same fidelity as an original dataset without having access to a critical basis set of the original?

Information theoretically speaking, this is impossible. The synthetic dataset will always have exploitable mathematical properties in a way non-synthetic dataset will not. It will open up the trained model to easy adversarial attacks.