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Solution looking for a use case, most likely, especially if it requires addition of hardware to existing cameras. There’s already lots of ways of fingerprinting

Solution looking for a use case, most likely, especially if it requires addition of hardware to existing cameras. There’s already lots of ways of fingerprinting camera + lens combinations and tying them to raw files + metadata, and lots of existing systems for automatically capturing originals and tagging derivatives of those originals. Those already have credence with the courts, it’d be an uphill battle to overcome that momentum without a hell of a value add… not sure a blockchain actually is that add.

sryanpdx 1y ago
You're right that existing fingerprinting methods (sensor noise patterns, lens artifacts) work for tying images to specific hardware, and courts do accept those. Where I see gaps: 1. Existing methods require forensic expertise - Sensor fingerprinting needs specialized analysis. Courts accept it, but it's not instantly verifiable by anyone. Expensive and time-consuming for routine authentication and difficult to automate 2. Derivative tagging systems depend on trusted intermediaries - News organizations, stock photo agencies, etc. Works great until you need to verify images outside those systems. Independent journalists, citizen journalists don't have access 3. The deepfake problem is accelerating - Existing forensic methods struggle with AI-generated content. Detection is always playing catch-up with generation. Courts may need higher standards as manipulation gets easier The blockchain value-add I'm proposing: - Instant binary verification (hash matches or doesn't - no expertise required) - No trusted intermediary needed (public ledger anyone can check) - Established at capture (before manipulation is possible) Your point about hardware addition is valid though. Secure elements are already in many modern cameras for other purposes (DRM, wireless security), so marginal cost might be lower than it seems. But I agree that retrofitting existing cameras is likely impractical. Real question: Is the gap between "forensically provable with expertise" and "instantly verifiable by anyone" worth the additional complexity? Maybe the answer is no. Existing systems work well enough for professional contexts where authentication matters. Would be curious if you've seen situations where current methods failed or were inadequate?
- yawpitch 1y ago
  Well I’ve worked in photography and cinematography, and some of that has involved legal and forensic contexts, and I’d say that for most purposes, pre-AI, there’s not really a gap that is about authentication… there’s a need to know of image B was derived from image A, but usually that’s a qualitative decision based on chain of custody (usually whomever has the earliest / rawest / highest quality original or primary reproduction master wins) not a quantitative thing based on hashing, especially as the hash changes from capture to use (especially when hashing the image + metadata and not just the image data itself). There’s more need for copy-robust steganography (for example, a watermark that’s invisible to humans but which AI cannot fail to introduce would be a trillion dollar technology) than there is a known and exploitable gap around who captured an image and what chain of images derived from that. If you work with raw data from original camera file and DNG for your various intermediate works (easily done with Lightroom / Darktable etc) you’re already able to maintain what is effectively a Markov chain through the simple act of keeping all your files backed up. Admittedly walking back from a low resolution copy on some Chinese t-shirt to the original camera file isn’t exactly easy, but it’s also relatively rare that it needs to happen. I would say there probably is a gap in some areas I don’t know well… medical and forensic imagery, for instance, and law enforcement evidentiary chains. If your system was ubiquitous and free could the FBI coming across a WebP of apparent CSAM on the dark net be connected back to a specific camera file, with a specific date and time stamp, establishing quantitatively that the subject and the photographer and the consumer are all tied by a verifiable chain of possession? If so, well there’s societal good (and potential bad) arguments for it, but for it to be really useful it would need to be mandated inclusion in the cameras themselves. For commercial photography I think you’ve got the problem that this is already relatively addressed. For a post-generative AI world it’s not clear how proof of authorship of what would have to be training data would be discernible from the deepfake content (absent that robust watermark idea, which would already make you rich beyond need). But in certain extremely specific workflows where chain of custody is really and ubiquitously important (medical records, legal evidence, educational materials, museum reprophotography, etc) there may be a market, but it would be very hard to validate without finding narrow experts.
  - sryanpdx 1y ago

sryanpdx 1y ago

You're right that existing fingerprinting methods (sensor noise patterns, lens artifacts) work for tying images to specific hardware, and courts do accept those. Where I see gaps: 1. Existing methods require forensic expertise - Sensor fingerprinting needs specialized analysis. Courts accept it, but it's not instantly verifiable by anyone. Expensive and time-consuming for routine authentication and difficult to automate 2. Derivative tagging systems depend on trusted intermediaries - News organizations, stock photo agencies, etc. Works great until you need to verify images outside those systems. Independent journalists, citizen journalists don't have access 3. The deepfake problem is accelerating - Existing forensic methods struggle with AI-generated content. Detection is always playing catch-up with generation. Courts may need higher standards as manipulation gets easier The blockchain value-add I'm proposing: - Instant binary verification (hash matches or doesn't - no expertise required) - No trusted intermediary needed (public ledger anyone can check) - Established at capture (before manipulation is possible) Your point about hardware addition is valid though. Secure elements are already in many modern cameras for other purposes (DRM, wireless security), so marginal cost might be lower than it seems. But I agree that retrofitting existing cameras is likely impractical. Real question: Is the gap between "forensically provable with expertise" and "instantly verifiable by anyone" worth the additional complexity? Maybe the answer is no. Existing systems work well enough for professional contexts where authentication matters. Would be curious if you've seen situations where current methods failed or were inadequate?

yawpitch 1y ago
Well I’ve worked in photography and cinematography, and some of that has involved legal and forensic contexts, and I’d say that for most purposes, pre-AI, there’s not really a gap that is about authentication… there’s a need to know of image B was derived from image A, but usually that’s a qualitative decision based on chain of custody (usually whomever has the earliest / rawest / highest quality original or primary reproduction master wins) not a quantitative thing based on hashing, especially as the hash changes from capture to use (especially when hashing the image + metadata and not just the image data itself). There’s more need for copy-robust steganography (for example, a watermark that’s invisible to humans but which AI cannot fail to introduce would be a trillion dollar technology) than there is a known and exploitable gap around who captured an image and what chain of images derived from that. If you work with raw data from original camera file and DNG for your various intermediate works (easily done with Lightroom / Darktable etc) you’re already able to maintain what is effectively a Markov chain through the simple act of keeping all your files backed up. Admittedly walking back from a low resolution copy on some Chinese t-shirt to the original camera file isn’t exactly easy, but it’s also relatively rare that it needs to happen. I would say there probably is a gap in some areas I don’t know well… medical and forensic imagery, for instance, and law enforcement evidentiary chains. If your system was ubiquitous and free could the FBI coming across a WebP of apparent CSAM on the dark net be connected back to a specific camera file, with a specific date and time stamp, establishing quantitatively that the subject and the photographer and the consumer are all tied by a verifiable chain of possession? If so, well there’s societal good (and potential bad) arguments for it, but for it to be really useful it would need to be mandated inclusion in the cameras themselves. For commercial photography I think you’ve got the problem that this is already relatively addressed. For a post-generative AI world it’s not clear how proof of authorship of what would have to be training data would be discernible from the deepfake content (absent that robust watermark idea, which would already make you rich beyond need). But in certain extremely specific workflows where chain of custody is really and ubiquitously important (medical records, legal evidence, educational materials, museum reprophotography, etc) there may be a market, but it would be very hard to validate without finding narrow experts.
- sryanpdx 1y ago