Technology

‘Image ballistics’: Your smartphone camera reveals more than you think


Remember the last time you watched analogue television? If the channel was slightly off, the screen would be filled with “snow” or white noise.

Although you can’t often see it with the naked eye, almost every image you take with your smartphone camera also has “noise” in it.

Not serious enough to upset your Instagram feed, these imperfections can be useful for a different group: law enforcement.

There’s one type of noise, known as photo-response non-uniformity (PRNU), that can help police identify devices.

This type of digital forensics has been applied in courts internationally in cases involving child exploitation material, and could also be used to detect things like digital forgeries.

Dr Lei Pan, a lecturer at Deakin University’s School of Information Technology, compared it to the work of a ballistics expert: the person who examines a firearm and works out whether the shot trajectory matches the crime scene.

In fact, your smartphone camera can be almost as revealing.

Finding a phone’s fingerprint

Your digital photos are full of information: an image’s metadata can typically show where and when a photo was taken.

It can also disclose the camera’s make and model.

But how do we know it is the exact same camera that took the photo and not just the same model?

That is where PRNU can help. The unique result of imperfections caused during the camera’s manufacturing process, Dr Pan characterised it as “the fingerprint of a camera”.

To understand how this fingerprint works, you must go inside the device, into the camera’s sensors.

“The image sensor is broken up into little photosites,” explained Richard Matthews, a PhD candidate researching digital image forensics at the University of Adelaide.

A photosite is a cell in the sensor that detects light, and a camera sensor can have millions of them.

“Each one of those photosites ideally would react in exactly the same way. But … there are slight variances,” he added.

Because of sensor imperfections, a photosite in the top left-hand corner of the image sensor, for example, would not necessarily react in the same way as one in the bottom right.

A PRNU fingerprint can be extracted from a large sample set of images known to be taken with the camera in question.

A filter is then used to create a noise-free image, which is subtracted from the original so all that is left is the noise.

“Then we average a large sample of these noise residues — the left-over noise — and all the other aspects of noise cancel each other out and we’re just left with a PRNU,” Mr Matthews explained.

If it is the same camera, then the PRNU should match the suspect image.

What else can PRNU do?

Don’t worry about PRNU affecting your photo quality.

“As far as the manufacturer is concerned, [the sensors] are uniform. We’re talking very low percentages here,” Mr Matthews said.

Smartphone brands are increasingly using software to alter photos or correct image flaws.

Facebook, for example, strips metadata out of pictures uploaded to its platform as a privacy precaution, but it is not entirely clear whether Instagram filters, for instance, would affect an image’s PRNU.

Deep learning techniques that generate fake images are also an emerging challenge.

Nevertheless, the uniqueness of your smartphone camera is a tempting feature to exploit for technologists.

Some have proposed using it as a method of smartphone verification, but your camera’s imperfections could have other uses.

In January, Gizmodo spotted a patent filed by Facebook in 2015 that outlined a process for using lens scratches or pixel flaws as part of its friend recommendation tool.

If the defects appeared in the same spot on two photos, they may have been taken by the same camera, and the two people may know each other.

This would not be enough for law enforcement, Mr Matthews suggested, which has a high standard of chain of custody.

“You can’t necessarily say all these photos belong to that user because that phone might have been sold,” he said.

However, this information could be compared with a photo’s metadata location and help analysts come to an estimation of its origin.

Ultimately, smartphones may look the same, but with the right tools, they are also incredibly unique.

Original article from http://www.abc.net.au/news/science/2018-02-07/image-ballistics-your-smartphone-camera-reveals-more-than-think/9397830

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