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Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

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Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#51

Post by smt88 »

cphoover wrote: post #28
smt88 wrote: post #27

Earlier quoted context omitted.

I worry about the same thing. I think "blockchain" (or even just a signed, immutable, public database) is mostly a solution in search of a problem, but I do think it may have an application here. If you can hash a video when it's recorded and publish the hash with a timestamp that can't be forged, you can at least prove that this video existed at least as long ago as that stamp. That allows you to invalidate any deep…

You can have an immutable centralized/federated system without using "crypto" though "proof-of-work", there are databases out there that provide immutable storage that don't require this overhead. Providing api access to a signed immutable database makes sense... but I'm not sure how much sense utilizing existing popular cryptocurrencies would make (e.g. bitcoin, etherium)

You need cryptography for hashing and verifying the integrity of any copy of the database.

You probably don't need proof of work, you're right.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#52

Post by smt88 »

prometheus76 wrote: post #41
smt88 wrote: post #27

Earlier quoted context omitted.

I worry about the same thing. I think "blockchain" (or even just a signed, immutable, public database) is mostly a solution in search of a problem, but I do think it may have an application here. If you can hash a video when it's recorded and publish the hash with a timestamp that can't be forged, you can at least prove that this video existed at least as long ago as that stamp. That allows you to invalidate any deep…

In that scenario, where is the line between a deepfake and satire?

That's an irrelevant issue. The issue I'm talking about is only whether a viewer can determine if a video has been edited.

Once they know it's edited, they can decide for themselves whether it's enjoyable satire or an attempt to deceive them.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#53

Post by jka »

Hey - great and important idea.

Have you discussed / looked into sampling environmental radio noise at various frequencies and locations and then interpolating samples of them within the video and audio itself at recording-time?

(ideally along with some kind of near-unfalsifiable timestamp signals and/or device keys to confirm that "yes, this unique device was here at this time and the proof is within the pudding)

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#54

Post by [deleted] »

Geee wrote: post #29

We have solved this problem already for text with digital signatures. There might be a way to digitally sign speech in real-time and show the signature on a display device, which is captured on video. It could be just a smartphone app or a separate device. This way every video could be proven authentic, even if they originate from unofficial sources.

[deleted]

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#55

Post by asail77 »

Geee wrote: post #29

We have solved this problem already for text with digital signatures. There might be a way to digitally sign speech in real-time and show the signature on a display device, which is captured on video. It could be just a smartphone app or a separate device. This way every video could be proven authentic, even if they originate from unofficial sources.

We hope a standard will be created and used by all digital content creation tools. But this will take time. And even then, bad actors will not be deterred. They will find ways to create fake content and pass it as authentic. We want to be there to fight them every step of the way!

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#56

Post by asail77 »

sigil wrote: post #46
ChefboyOG wrote: post #44

Earlier quoted context omitted.

I think the point is that yes, that seems like a good solution for verifying content that purports to be released by a certain creator, but it doesn't solve the problem of deep fakes for captured footage i.e. you can prove it isn't a video that you created, but you can't prove it isn't a video someone else took of you.

That makes sense. But if signed AV takes off, the video someone else took of you and shared likely bears their seal. And audiences decide how much they trust that source – just like they look for a CNN / BBC / etc logo in the corner currently.

Great discussion. Many have asked the same questions.

We hope a standard will be created and used by all digital content creation tools. But this will take time. And even then, bad actors will not be deterred. They will always find ways to create fake content and pass it as authentic. We want to be there to fight them every step of the way!

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#57

Post by asail77 »

atlasunshrugged wrote: post #49

This is super cool, you should chat with the folks in Estonia who had worked on developing Sentinel ( https://thesentinel.ai/ ) which had a similar premise but ended up pivoting. I advised them for a bit, happy to chat too (email in bio). Edit to include link to their website

Awesome! We will look them up! And happy to chat with you. You can also email us at ask@realitydefender.ai

Thank you!

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#58

Post by rdrdg »

huynhhacnguyen wrote: post #37

First of all, congratulations on the lauch! Your description about the "model of models" and combining their scores is really intriguing. Detecting deepfake is an interesting topic on its own and apparently there are lots of use cases that I'm not even aware of, partly due to my limited knowledge in this subject. There are a few points of I'm curious about (Beware that the following questions can be very silly, comin…

Thanks for your questions.

- The input to our models are image, video, and audio. Based on the model, we can use parts of the image (esp faces) or whole image. Yes, we also incorporate metadata for better detection.

- It's a fair concern. As quality of generative media increases, so does the sophistication of detection. Since, we fully understand how generative media is created, it gives our the leverage to reverse engg. Much like the anti-virus industry (wrt scanning), we'd need to be at the forefront of not only detection, but generation methods, re-learn models based on new generation methods, etc.

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#59

Post by rdrdg »

jka wrote: post #53

Hey - great and important idea. Have you discussed / looked into sampling environmental radio noise at various frequencies and locations and then interpolating samples of them within the video and audio itself at recording-time? (ideally along with some kind of near-unfalsifiable timestamp signals and/or device keys to confirm that "yes, this unique device was here at this time and the proof is within the pudding)

Currently, we are consider image, video and audio data types. This multi-modal idea sounds interesting none the less, thanks for sharing :)

Re: Launch HN: Reality Defender (YC W22) – Deepfake Detection Platform

#60

Post by rdrdg »

ChefboyOG wrote: post #43
calvinmorrison wrote: post #42

Earlier quoted context omitted.

Of course, because these companies are probably owned by the same people in the end that develop the DeepFake datasets, generating endless income from both sides. It's like ADA Compliance lawsuits. I can't prove the AccessaBe or other "ADA Compliance" web tooling are generating these lawsuits, but their company would not exist without them. Why wouldn't they want more lawsuits?

The majority of large, popular datasets in deep learning are curated and hosted by academics: https://paperswithcode.com/task/deepfake-detection#datasets

Thanks, yes, we benchmark on these research datasets as well.
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