For instance, sensor noise should be rather consistent if the photos were taken with the same camera, pretty much like firing a handgun and the bullet gets unique marks.

Bingo - that's right on the money.

There are two aspects research aspects that I'm familiar with when I worked in this area in 2006-2007. The first was the identification of the make and model of the camera and the second was identifying if a specific camera took a specific image.

Here's a few relevant links:

• Digital Cameras Have Unique Fingerprints, Schneier on Security
• Binghamton University research links digital images and cameras
• Forensic Camera Classification: Verification of Sensor Pattern Noise Approach

Given a large sample of images from multiple cameras, I can produce an average noise pattern that exists on a given make and model. When provided with a single image, I can use this average noise pattern and the single image to, with high confidence, tell you the make and model of a given camera.

Given a sample of images from a single camera, I can compare a single image to the noise pattern from this sample of images and tell you if the camera that produced the large sample also produced the single image.

However, the algorithms and techniques to do this are patented. I believe US Patent 7,616,237 is relevant to your particular question. It cites the work of Jessica Fridrich, Miroslav Goljan, and Jan Lukas and also provides a number of research papers on the subject. Unfortunately, I'm not familiar with any publicly available software (commercial or otherwise) that implements this technique. The work that I was doing was on behalf of the US Department of Defense, who supported the research that went into this patent.