I think the noise mentioned here is refering to in the basic sense flaws in the pixelation.

So, I think the next step would be to get a bunch of cameras (or images known to be taken from specific cameras) all of the same make and model and test tons of images till you could find a similarity in all of them, This would be like the caliber that you would use to describe in tracing a bullet back to the original gun. Of course the downside would be that you would need to do this for each model of camera. But once you have the general variations you would always have those as blueprints.

Then after you find the similarities or a constant thread that is only found in that specific camera model you can start to decipher between each camera of that model. Now just like guns you really don't need to have an analysis of each camera, just so you can tell between the brands as far as big noise (flaws) and then the more specific noise (unique to only a single camera).

Esentially telling between multiple brands of cameras would be the easy part. Deciphering between two or three cameras of the same brand and model is where the real forensics comes in to play. Especially after you factor in the thousands of cameras there are for each model.