[HN Gopher] Camera model identification based on forensic traces
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Camera model identification based on forensic traces
Author : a1eaiactaest
Score : 25 points
Date : 2022-07-04 11:30 UTC (1 days ago)
(HTM) web link (www.sciencedirect.com)
(TXT) w3m dump (www.sciencedirect.com)
| cm2187 wrote:
| How does that help? It's like identifying in which continent a
| picture was taken.
| semi-extrinsic wrote:
| I'm sure it will be useful for law enforcement or a defense
| attorney, if someone is on the record saying "I took this image
| with my Model Z camera" and they can prove that's a lie, it
| brings the rest of that persons testimony into doubt.
| runlevel1 wrote:
| I expect it's similar to knowing the make and model of a car
| that was used in a crime.
|
| Police aren't going to go around pulling over every one of
| those cars. However, if a suspect is captured, it can be a
| datapoint to help make the case.
| bad416f1f5a2 wrote:
| > However, if a suspect is captured, it can be a datapoint to
| help make the case.
|
| The paper talks about using this to go after people who are
| creating CSAM. That's a federal crime, which means an
| investigation will be conducted by federal agents. USAs have
| a 93% conviction rate - they'll case build like crazy to
| ensure they get a conviction. Any data point helps.
|
| Plus, they might ask you if you took a photo with your phone
| - say "no" and they prove you did, and you're also lying to
| the feds, which is a felony itself.
| kortex wrote:
| Hardly. There's 7 continents (~3 bits of entropy), but
| dozens/hundreds of camera models this technique (6-8 bits). And
| it's hardly the only media forensic technique out there.
| There's ways of extracting the time of day without metadata,
| manipulation software chain, the lens used (sometimes down to
| make and model), and tons more. Before you know it, you've put
| a big dent in the ~33 bits needed to pinpoint a specific
| person.
| aeturnum wrote:
| There are no single perfect solutions. Being able to identify
| which continent a photo was taken in would often be useful.
| Geolocation, even inexact geolocation, is an essential part of
| intelligence work.
| cm2187 wrote:
| my point is that there are hundred of millions of users using
| the same iphone camera. That looks like a very minor
| datapoint to me.
| anigbrowl wrote:
| It's a point of correlation. Suppose you know person X in
| your area has a tattoo of a skull on their right arm,
| smokes Marlboro red cigarettes, is left-handed, and uses an
| iPhone, and all this information is fairly recent. You
| notice someone with a skull tattoo and decide to observe
| them, the three minor details take the id from a possible
| to a probable.
| Ancapistani wrote:
| True - but I might be the only person in my county using a
| Fuji X-Pro3.
| d4a wrote:
| I could have sworn I read about this exact thing in Cory
| Doctorow's novel Little Brother
| Wistar wrote:
| Can an image be completely re-created with an AI routine or
| process that yields very high visual fidelity to the eye but
| eliminates any camera signatures?
| ampamp wrote:
| yes! https://arxiv.org/abs/2002.07798
| BLO716 wrote:
| I'd say also if this interests you - checkout #OSINTION
| #blackbadge training from Joe Gray!
| https://www.theosintion.com/courses/ (also, I am not Joe Gray -
| just lots to be learned from this category of investigation)
| sharmin123 wrote:
| radarsat1 wrote:
| I think an interesting possible application of this is that a lot
| of applications of video to 3D reconstruction, such as SLAM and
| photogrammetry, require good camera intrinsics as calibration
| input. Getting this information automatically seems to be
| difficult, so lens calibration is an important step. This work
| suggests to me that calibration information could either be
| recovered directly from images, or the correct entry could be
| automatically looked up in some large shared database, which
| would really simplify things for certain applications.
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