[HN Gopher] Deepfake detector can spot a real or fake video base...
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Deepfake detector can spot a real or fake video based on blood flow
in pixels
Author : sizzle
Score : 52 points
Date : 2022-11-18 18:47 UTC (4 hours ago)
(HTM) web link (www.zdnet.com)
(TXT) w3m dump (www.zdnet.com)
| atonse wrote:
| Love the cat and mouse game!
|
| So then this will be the next target of better deepfake models,
| right?
|
| We saw that fake pharma tweet that (supposedly, but not really)
| sent the stock crashing - how long before a fake video of a CEO
| making an announcement at a fake Davos-like conference stage
| interview?
|
| As a techie, is this going to make things like digital signatures
| more important? But more realistically though, most of the
| audience that would do impulsive things won't care to verify.
| notacoward wrote:
| HN story a month from now: new deepfake software can evade
| Intel's detector.
| yieldcrv wrote:
| That's a great observation to make deep fakes more realistic
|
| I often think about subtleties that throw us off a little, too
| bad that disclosing this subtlety reduces the ability to discern
| dahdum wrote:
| Can this technology eventually detect their heartbeat, or is it
| just looking at slower changes over time? If the latter it sounds
| much simpler to defeat, if the former that would have many
| repercussions.
|
| Live heart rate by video analysis would make things like
| televised court proceedings, congressional hearings, and news
| interviews much more invasive. Elevated heart rate is a sign of
| stress, and it wouldn't be long before people were jumping to
| conclusions over whether someone was lying or hiding their true
| feelings/intentions.
| sbirch wrote:
| This has actually been done before, awhile ago:
| https://people.csail.mit.edu/mrub/vidmag/
| dahdum wrote:
| Very cool, thank you. I'm honestly surprised this dark magic
| hasn't been (ab)used yet, unless it has some strong
| limitations.
| ehsankia wrote:
| Not sure if it's quite the same, but Google Fit has a feature
| that gets your respiratory rate from the selfie camera. They
| also have one where you put your finger on the camera flash
| and it uses that to see your bloodflow.
|
| https://www.lifewire.com/measure-respiratory-and-heart-
| rates...
| lattalayta wrote:
| Simulating blood flow is a technique currently used in high-end
| VFX animation for movies.
| https://www.fxguide.com/fxfeatured/maleficent/
| alteriority wrote:
| If the filter doesn't notice blood flow on a non-deepfaked
| subject, run.
| Mountain_Skies wrote:
| Or we find out that certain population groups have different
| blood flow patterns, which the system incorrectly identifies as
| proof of fakery. Or perhaps for some, it's simply not
| detectible even though they are real live people.
| AustinDev wrote:
| Or we find out some people have dark skin and the blood flow
| isn't visible to the camera in these situations.
| maxbond wrote:
| Yeah, neither deepfakes nor deepfake detectors will end
| epistemology. We'll need to use a multiplicity of tools, with
| strengths and weaknesses known and unknown, and come to a
| conclusion based on the preponderance of evidence knowing
| full well we will sometimes get it wrong.
| johnwheeler wrote:
| For now...
| phonebucket wrote:
| Pet peeve of mine: articles using stats like 96% accuracy.
|
| If the test set had 4% deep fakes, and 96% legitimate videos, a
| model which always predicts legitimate video would score 96%
| accuracy, even if it were useless.
|
| Stats like precision, recall, F1 scores etc. are important.
| asow92 wrote:
| enhance blood flow in 3... 2.. 1.
| skunkworker wrote:
| Won't this be used in the next deepfake as an adversarial network
| in order to produce more realistic results? It's an endless cat-
| and-mouse game.
| mumumu wrote:
| This is probably intended for encoding webcam chat between
| Intel devices. They can hash the video "frames" to detect
| interception.
| rogers18445 wrote:
| > It's an endless cat-and-mouse game.
|
| This is often stated but I think it has to be obviously wrong.
| This isn't a traditional interactive game such as malware &
| anti-malware.
|
| You have existing sensors which operate under the constraint of
| [ real world -> theoretic pixel space -> optics & aberrations &
| sensor noise -> compression ]. And a single adversary which
| attempts to fake this chain.
|
| The detection of fakes isn't even an adversary in this game,
| it's merely a detection of deviation of the faking process.
|
| At some point, probably soon, the faking process will reach a
| point where any deviation will be drowned out by the noise
| aspect of optics & sensors & compression.
| halpmeh wrote:
| One method of generating things via neural networks is called
| a generative _adversarial_ network. It works by having two
| models. One that generates content and one that detects fake
| content. You train them both in parallel. As the fake
| detector gets better, so does the generative model at
| generating fakes. It's literally a cat-and-mouse game. If
| someone came up with a scheme to reliably detect your fakes,
| you could add it to your discriminator model and retrain the
| generator to improve the fake generation.
| rogers18445 wrote:
| My understanding is that it's not quite that simple. GANs
| have stability problems (and as a result somewhat out of
| favor atm) and if the fake detection mechanism isn't a
| differentiable function itself no training can happen.
| sigmoid10 wrote:
| The fake detection mechanism (aka discriminator) is
| usually just another neural network and I bet that's the
| case here as well. So it must be differentiable and thus,
| if anyone ever gets a hold of it, it could be easily used
| to train a generator that will eventually fool the
| discriminator.
| AustinDev wrote:
| >It's an endless cat-and-mouse game
|
| Yes, this is the way with anything software based that can earn
| people money.
|
| See: video game hacks, SEO manipulation, etc
| yreg wrote:
| But especially so when machine learning is involved since a
| model can train off its adversary.
| BoorishBears wrote:
| Not really special in the case of ML.
|
| Before deepfakes, if you wanted to claim a video was
| doctored in court, you'd find an expert on video editing
| and have them testify.
|
| But the same knowledge that allowed them to identify a
| doctored video (like 50hz/60hz hum) could be in an
| adversarial manner to create a very convincing video.
|
| At most deepfakes democratize that "knowledge" in the form
| of a model, so it still works both ways.
| [deleted]
| squarefoot wrote:
| I hardly believe it could work on media uploaded on YT and
| similar platforms, and assuming it does, it would be easily
| defeated either by over compressing the videos so that subtle
| chromatic changes are eliminated or applying smoothing filters
| before reuploading. Should the technology catch on, it's just a
| matter of time before the appearance of filters that scramble
| those subtle differences, masking them for example as a grain
| filter effect, to make it useless.
| lowbloodsugar wrote:
| For now.
| pestkranker wrote:
| I'm sure that one day, most of the things we'll see or hear on
| the web will be filtered by this kind of software.
| progrus wrote:
| Not likely IMO, the arms race will continue.
|
| Plus, are you sure you're eager to sign up for even more
| censorship-by-opaque-algorithm?
| mumumu wrote:
| This is not new. It is news because it's from Intel.
|
| I looked into that a year or two ago and there were papers on the
| this.
|
| Anyone who is familiar with Euler Video Magnification and with
| neural network likely though of that.
|
| Does this work in encoded videos? I doubt. Intel probably can add
| a a feature the video encoder and sell it as an authentication
| service for webcam communication on Intel Plataform.
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