Detecting Faked Photographs Gets Easier

nusratt writes "Some years ago, an issue of 'Whole Earth' had a convincing cover-photo of a flying saucer cruising low over downtown San Francisco in broad daylight. The accompanying feature article proclaimed that photographs can no longer be trusted as evidence of anything, because of the ease of doctoring images digitally and undetectably. Now, Dartmouth Professor Hany Farid and graduate student Alin Popescu 'have developed a mathematical technique to tell the difference between a "real" image and one that's been fiddled with.' Farid says, 'as more authentication tools are developed it will become increasingly more difficult to create convincing digital forgeries'." There's also an NYT story.

Comments

Seamless Math Next?

[mfh]

While it may become increasingly difficult to forge digital images, and even forge hard currency, the result could be of two possibilities;

1. Forgers get smart and use older cameras to take a picture of a digital forgery to pass as an original, using blurring techniques offered by physical means and lens... etc (easy)
2. Forgers quit being forgers (unlikely)
3. Alteration technologists create armor against image forgery detection algorithms (possible)

For me, I think any time spent trying to beat the detection of forgeries would be a good thing in terms of art and creativity -- not to mention the possibility of better digital growth algorithms to join layers mathematically seamlessly (which could be used in games and simulation engines for better realism). However, law enforcement agencies might try to combat the circumvention of forgery detection by charging people with crimes for only trying to make their images more realistic and improve technology. It's a messy issue, that will sort itself out over time.

In Doom 3 Bloopers, a mod I've started on, I am looking at ways of integrating realworld imagery into the mod, and this detection stuff could actually help me to better integrate my own art and images if I can find a way around it. Let's face it, if the math says it's an original, the human eye will be fooled, which is the goal of most video game design. If anyone wants to help along those lines, they should contact me!

Re:Seamless Math Next?

[Anonymous Coward]

I gotta say, while the first half of your comment was certainly insightful, that was one of the most blatant attempts to force your pet project into an unrelated comment I've ever seen!

You, sir, have balls!

Re:Seamless Math Next?

[Ieshan]

It seems as though the algorithm they have works on the fact that there's some statistical difference between a real image and a faked one, but not 100% of the time.

Why wouldn't someone simply build a filter into a program that changed bits in an image until it passed a check by their algorithm - on failing, it would simply go back and change more appropriate bits?

Seems as though it would be a computationally intensive but a logically easy task.

Re:Seamless Math Next?

[yintercept]

My first thought on the article was the same. The mathematical tests to determine fake photos will have value only until the fake photo industry builds the tests into their software. For that matter, I suspect that the main use of the Hany Falid method will be to make your fake photos even more realistic.

The most interesting line in the article was:

but computers make it easier for more and more people to manipulate images.

One could read into these lines that the ability to fake photographs was great until anyone could do it. Now that we know how easy it is to fake photographs, we no longer implicitly trust messages...but we will trust mathematically authenticated fake photographs because math is infallable.

Re:Seamless Math Next?

[freshmkr]

Let's face it, if the math says it's an original, the human eye will be fooled, which is the goal of most video game design.

Don't be so sure about that!

I don't know what these researchers are doing, but I can venture a guess. You can think of an image as being composed of a large set of superimposed sine waves---they look like this. To figure out what sine waves make up an image, you do a Fourier Transform, which is well documented on Google.

Natural images contain a characteristic power spectrum: some frequencies--lower ones--tend to occur quite often, while others--higher frequencies--are less common. The spectrum is actually pretty regular across an image set. I'm betting, though, that fake images don't respect this power spectrum and lead to detectable anomalies.

But beware! You can have completely bogus images that also respect the power spectrum. Some researchers at MIT (Torralba et al.) use power spectra to successfully detect different image environments, e.g. indoors, outside in a city, out in the country, etc., but in the papers they show some images that have been reconstructed from their spectral models.

You would not be fooled. They look like finger paint pictures.

--Tom

Re:Seamless Math Next?

[B'Trey]

One could read into these lines that the ability to fake photographs was great until anyone could do it. Now that we know how easy it is to fake photographs, we no longer implicitly trust messages...but we will trust mathematically authenticated fake photographs because math is infallable.

Or you could read into them that when it was rare and difficult to fake photographys, most of the photographs you saw were genuine, so you could place a decent amount of trust in what you were seeing. Now that faking photos is easy and commonplace, you can no longer place much trust in photos. With mathematically verified photos, you can place more (though not complete) trust back in the photo. It isn't foolproof but the level of assurance is significantly higher.

Re:Seamless Math Next?

[Megahurts]

One could read into these lines that the ability to fake photographs was great until anyone could do it. Now that we know how easy it is to fake photographs, we no longer implicitly trust messages...but we will trust mathematically authenticated fake photographs because math is infallable.

Or you could read into them that when it was rare and difficult to fake photographys, most of the photographs you saw were genuine, so you could place a decent amount of trust in what you were seeing. Now that faking photos is easy and commonplace, you can no longer place much trust in photos. With mathematically verified photos, you can place more (though not complete) trust back in the photo. It isn't foolproof but the level of assurance is significantly higher.

Or you could realize there's inherent error in any statistical method, and that with a little bitof foresight, this error could be expoited to provide false results. The best detector of falsified photography is still a well-trained human eye. The key to knowing whether or not to trust images is to train your eye.

Re:Seamless Math Next?

[NanoGator]

"Seems as though it would be a computationally intensive but a logically easy task."

Probably. Consider this, though: Fingerprints are common knowledge. We ALL know that if we commit a crime, fingerprints will be lifted to try to catch us. There are well known ways to defeat this, but remarkably, LOTS of people are still leaving fingerprints as clues at a crime.

I hope you can forgive me for reading a little more into your post than you actually said. I don't know for sure if you were going the "this could easily be defeated, thus it is ineffective" route. But I thought this would be as good of time as any to mention this.

Re:Seamless Math Next?

[yintercept]

when it was rare and difficult to fake photographys

It was never rare nor difficult to "fake photographs." From the very moment photography existed, people realized that they could control the message the photograph carried. Most of the early photographers had studied optics and developed their own film and manipulated images accordingly.

Most of the early photos you come across were staged. Taking a photograph was a big deal. People dressed up in their best outfits and the photographer would construct the scene. Often the photographer colored or otherwise enhanced the image. Photography has always been an art form. As an art form, people choose the message to convey.

Using photographs as evidence has always been problematic. The struggle is for lawyers to keep enough faith in photos to be able to use them in court. Personally, I think having a method to declare a photography mathematically correct immediately creates a problem where people with sufficient resources to fake mathematically correct fake photos will have the ability to manipulate the courts.

There never was that much faith in photographic evidence. I think we are better of having doubts about photographic evidence than we will be if we sanctify any photos as mathematically correct. The methods will have some value in quickly identifying tampered evidence, but will not have value in verifying it.

Re:Seamless Math Next?

[B'Trey]

OK, if we're going to have this conversation, we need to define what we mean by "fake photograph." Yes, many photos were staged, particularly when taking photos was significantly more difficult than "point and shoot." But a staged photograph is not a fake photograph - it's still a reasonably accurate representation of reality as it existed at the time the photo was taken.

You're also quite correct that photos are routinely manipulated in the dark room. However, manipulating the color and otherwise enhancing the image is not at all what most people mean by a "fake photograph." There's a fundamental difference in those types of manipulations and putting Sarah Michelle Gellar's head on a porn star's body or putting John Kerry and Jane Fonda on the same podium together. This type of thing was possible before, but it was much, much more difficult and much less common.

Re:Seamless Math Next?

[angst_ridden_hipster]

At the Getty Museum, they recently had an exhibit of influential photographers and the history of photography (http://www.getty.edu/art/exhibitions/genius/).

One example photo from the beginning of the last century or before, depicted two figures by a lamppost on a foggy Parisian street. I took it for an unaltered print, but it turned out to be a composite of seven [!] separate images. It was laboriously done in the darkroom. It was incredible. (Unfortunately, I can't find the specific photo on their otherwise excellent site.)

Now, we've all seen great darkroom manipulation like the work of Jerry Uelsman (www.uelsman.net), but this particular picture was a hundred years older than his work. It was absolutely convincing.

I guess my point is, photographs have in fact been "faked" as long as there have been photographs.

Actually...

[julesh]

I think authentication tools make it easier. As someone who's tried a little photo manipulation in the past, I can tell you that the hardest thing is knowing when something's right. If you have an automated tool that can tell you when it's right, it becomes easier. Of course, that relies on the tools working...

Self Defeating

[Dozix007]

While an equation to make sure that a photo is not forged is all well and good, it is self deafeating. Just like simple encryption, which is good for people with simple problems, exploring the equation will yield a way to fool it. If you have someone who truely wants to forge a photo, they probably could still defeat the check.

Re:Self Defeating

[John Biggabooty]

I don't know what the big deal is. Old style film photos can be fiddled with, but digital photographs cannot be faked, and digital photography is taking over.

Re:Self Defeating

[ruszka]

Which makes me wonder.. did they create this in order to detect forgeries? or possibly to make it easier for the government to forge photographs and then use the technology to make those images "authentic"

Re:Self Defeating

[slavemowgli]

I know how cryptographic (and hashing) algorithms work.

As for "almost unbreakable" - well, that simply means that it *is* breakable after all; brute force does work, even though it's usually inefficient (which is why I added that an attacker would need a sufficient amount of time, energy and/or computing power).

Furthermore, from what I know, it is neither proven that your average hash functions (MD5, SHA1, RIPEMD-160 etc.) are collision-free nor that the underlying mathematical problems of your average asymmetric ciphers (RSA, DS, El Gamal etc.) indeed cannot be solved with less effort than brute force. (I may be wrong here, so feel free to correct me)

And lastly... you missed my point completely. :) What I really was saying was that the fact that there will be ways to defeat this system does not mean it is completely useless or obsolete. Without looking at the algorithm in detail, it's not even possible to say that there likely will be easy ways around it (common sense might dictate there are, but common sense also dictates that RSA is easily breakable - mine does, anyway). Ultimately, only time will tell just how feasible it is to defeat this system, and only that will determine just how useful it will prove to be on a given level. (As an example, I could very well imagine that an intelligence agency or a similar organization will be able to produce images that pass the test when necessary, for example, while your average Paintshop Pro user won't).

So much for my faked photo of Rumsfeld & Sadda

[The I Shing]

Now they'll be able to prove that my photo of Rumsfeld shaking hands with Saddam in 1983 is a fake.

Rumsfeld was really shaking hands with an alien, and Saddam was shaking hands with Elvis, but the resulting merger of the two photos was much more provocative.

Just a thought...

[julesh]

Farid and his students have built a statistical model that captures the mathematical regularities inherent in natural images.

I wonder if they've considered the potential applications in image compression?

I had developed a foolproof algorithm...

[Anonymous Coward]

...but it was only accurate when the photo contained an image of Admiral Ackbar.

What kind of digitized photos does this work on?

[multiplexo]

If I take a high resolution TIFF image and start mucking with it I can see how it would be easy to find the manipulations (especially if you're as thumb-fingered as I am with PhotoShop). However with most digital cameras using various compression schemes to store the images how can you tell what is a result of manipulation versus what is an artifact of compression and or digitization? Certainly some gross manipulations will be obvious compared to the properties of compressed images, but I would imagine at some point you'd be hard pressed to say "this image was deliberately manipulated" instead of "this is a compression or digitization artifact".

While this might not be a problem for gross manipulations (the faked John Kerry/Jane Fonda photo being a recent example) I can imagine a class of images where subtle manipulations caused great effects and were not readily distinguishable from compression artifacts.

Random set of pixels?

[MedHead]

I fail to see how an image can have a "random set of pixels" as the article suggests. With color and brightness balancing, the pasted areas of an image blend in with the rest of the image (especially when the artist uses Photoshop's clone brush to combine the two images). This sounds to me like the computer could very well throw out false positives for images that have extreme color or brightness differences.

Okay, but here's my question.

[Anonymous Coward]

Farid's algorithm looks for the evidence inevitably left behind after image tinkering. Statistical clues lurk in all digital images, and the ones that have been tampered with contain altered statistics.

That makes sense. However, it seems like these statistics would be based on very minor details. What happens if you run their analyzer on an image that has been altered by using lossy image compression, such as JPEG compression? Lossy image compression is designed to obliterate details humans wouldn't notice; some of these details might be significant to their statistical model. Would JPEG-compressing an image make it impossible to determine its veracity? Would their software just tag all JPEG images with compression below a certain threshold as being "unnatural" (since they have been, after all, digitally altered-- just not digitally altered in a content-relevant way...)

And don't some digital cameras use lossy formats such as JPEG as their native storage format?

Re:Okay, but here's my question.

[BillX]

Conversely though, I wonder if compression artifacts could be one of the very things the algorithm looks at. Your digital camera takes a picture, compresses it with JPEG and produces subtle (to the eye) artifacts. Now start moving things around in the image (lets assume for the moment you're not even grafting in UFOs), and now the artifacts have moved with them, and can be identified as not being where the JPEG algorithm would put them. Of course, to make it look convincing, you've probably used some smoothing, airbrushing, feathering etc. filters, which will have obliterated artifacts entirely in some places. Finally, suppose you do graft in a UFO--where does this picture come from, and does it have compression artifacts of its own? Even if it came from the same camera, differences in the images mean differences in the compression. But the UFO's probably been resized, rotated, etc., further messing up the artifacts. Of course, just like when you move stuff around in the same image, they're not going to match up anyway. I think this would be a very easy thing for an algorithm to look at.

Of course, you could just save the doctored foto itself as a low-quality JPEG - but a) if it's going in a newspaper, do you want low quality?, and b) you're still just adding your own artifacts to the original - it's going to be some pretty severe compression before they're undetectable.

Re:Okay, but here's my question.

[drinkypoo]

Compress your JPEG with three different encoders at subsequently lower quality settings until you reach the quality setting (and file size) you're looking for, and the artifacting will be effectively untracable. Unless there has only been one predictable compression pass since the manipulation, the lossy nature of JPEG should be sufficient to make it impossible to track the chain of encoders back to the source image data. (It's always impossible to achieve the original data, that's what lossy means, but you can likely get some good information about what it was encoded with by examining the resulting file.)

The unfortunate thing

[Anonymous Coward]

The article says the research is founded by the Department of Homeland Security. That means that despite the many useful possible aspects of this technology, it will probably never see the light of day. If the DHS is going to be using this technology to identify faked photos, it would be greatly in their interest for the full algorithm and its implementations to not be made available to the public-- since after all if people know what the DHS is using to determine faked photos, they can target the algorithm.

Now that I have written that, looking around, it appears I am actually wrong. If you look at Mr. Farid's personal page, it appears he will be publically presenting a paper covering the fakeness-detection algorithm. I hope the full algorithm will be presented to the academic community.

It will improve the fakes

[bhsx]

People making fakes of UFOs and breasts on the Olsen twins will discover new techniques to overcome the detection. It will always continue in a spammer/spam-filter fashion. I'm sure that we'll soon see tools to automatically take the mathematical principles into account and automatically correct fakes that can be detected.
But hey, I'm pretty sure this one pic of the Olsen twins I got from Kazaa is real anyway.

Why not *make* it real?

[over_exposed]

So if it detects digitally altered images, why can't we just 1) Alter the image to our heart's content 2) Print it on a high quality printer ($500- $2K at CDW) 3) Scan it back in with a nice scanner

Re:Why not *make* it real?

[Johnathon_Dough]

Print it on a high quality printer

The short answer is dot structure. All printers, (excepting Dye Sub) use some form of sparying of ink, or layering of screened images(halftone dots) Fancier does not necessarily mean smaller dots, it usually means more calibrateable and more consistent color. What you need is a film recorder, which will transfer your image to a negative or a slide, and currently, there are no digital cameras that will record an image at a high enough resolution for this to be flawless (about 40-100 pixels per millimeter), so you must start with a film camera and scan the image in at a high enough resolution. The typical rule of thumb for this kind of work would be one size up from what your end result would be. So if I wanted to create a faked 35mm slide, I would start by taking pictures with a 4x5" film camera scan and use that.

But yes, your point is sound. Technology will not fill the analog hole. Even in "digital" photography.

A more in-depth article

[asterism]

If you are looking for more detailed information, along with equasions, here is a link to one of their recent publications on the topic: http://www.cs.dartmouth.edu/~farid/publications/sp 04.html

MICHAEL, thanks for adding the . . .

[nusratt]

NYTimes story link, which is actually more informative and interesting than Dartmouth's own story. In particular, the instant that I started to read the NYT story, I dope-slapped myself for not having thought of the reverse implication of the technology, namely that it might be used to prove that a contraband image (such as child-porn) is NOT faked (and therefore is genuinely illicit).

Re:MICHAEL, thanks for adding the . . .

[julesh]

No, it couldn't. All it can prove is that if an image is fake it has been done very well.

If A doesn't conform to the statistical distribution of B, then A isn't B (with a high degree of confidence). But if does, that doesn't mean it is B -- you might just be looking at the wrong set of identifying features. I.e. not everything with two feet and a bill is an aquatic bird; it might be the waiter.

Re:What kind of digitized photos does this work on

[LiquidCoooled]

The easy answer to that lies in the original compression artifacts remaining - any new fragment/change will not keep these in a statistically similar fashion, and thats what my understanding of this software is.

Smudging a part of an image would remove these artifacts, and would be near impossible to reproduce - like the paper grain on a canvass oil painting.

practical use

[Slothy]

Run it on the goatse guy! If the results are positive I can finally start sleeping again.

Admissibility of Digital photographs as evidence?

[walmass]

There are stories about successful defense against digital photographs in criminal cases. "Enhancements" using photoshop can be considered evidence tampering. So this technique can have a life-altering implication for some people.

for those who want more information

[flynt]

Anyone who wants to know more can read the actual papers here: http://www.cs.dartmouth.edu/~farid/publications/ ...papers 1,2,4, and 5 seem to be what this research is about, but others probably cover it too.

NY Times Article Text

[Billobob]

for those who care about it...

For Doctored Photos, a New Flavor of Digital Truth Serum By NOAH SHACHTMAN

Published: July 22, 2004

From the material found on his hard drive, Bryan Sparks of Springfield Township, Ohio, seemed guilty when he was arrested in 2002. The sexually explicit pictures of minors appeared to put him on the wrong side of child pornography laws. But at his trial this spring, Mr. Sparks was acquitted because no one could tell for sure whether the images were authentic or just clever digital forgeries.

Mr. Sparks was eventually convicted on a separate charge of rape and sentenced to life in prison. But the uncertainties that surrounded his case, and others like it, are driving researchers to develop software that can automatically figure out which digital pictures are real and which ones are fake.

"It used to be that you had a photograph, and that was the end of it - that was truth," said Hany Farid, an associate professor of computer science at Dartmouth College who is a leader in the field. "We're trying to bring some of that back. To put some measure of guarantee back in photography."

At stake is more than the fate of possible child pornographers. The United States military has become increasingly reliant on digital images from drones and satellites to give soldiers a sense of the battlefield. Law enforcement officers routinely use digital cameras to photograph crime scenes. Newspapers and magazines are now dependent on digital photographs that can be easily doctored.

Over the last three years, Professor Farid and his students have become experts at forgery, making hundreds of images that look authentic but have in fact been digitally tweaked. License plate numbers are changed. A single stool standing on a checkerboard floor is suddenly a pair of stools. Dents on a car are wiped away with a few mouse clicks.

The skillful tampering disturbed the images in ways that the human eye could not detect. But Professor Farid says his algorithms can spot them and sound the alarm.

For example, when two images are spliced together - like the picture of a shark attacking a helicopter that has circulated around the Internet in the past few years - one or both of the original pictures usually has to be shrunk, enlarged or rotated to make the pieces fit together. And those changes, no matter how artful, leave clues behind.

Take a picture that is 10 pixels by 10 pixels, for a total of 100. Stretch it to 10 by 20 pixels, and image-editing software like Adobe Photoshop will assign the picture's original pixels to every other slot in the new picture. That leaves 100 pixels "blank," or without values. Image-editing software fills in the gaps by examining what their neighbors look like, and then applying an average. To oversimplify, if pixel A is blue, and pixel C is red, the blank pixel B will become purple.

This kind of averaging becomes "pretty obvious" after some analysis of the image, Professor Farid said.

In tests on several hundred doctored photos, this technique for detecting changes proved to be virtually foolproof if the picture quality was high enough. Uncompressed TIFF image files, which contain enormous amounts of data, were like an open book to Professor Farid's team.

But Professor Farid said that for now the technique does not work as well with files created in JPEG, the compressed picture format most commonly used online. As the size of a JPEG file shrinks, the correlations between pixels become much less obvious. "At 90 percent quality, it falls apart very quickly," Professor Farid noted.

Jessica Fridrich, a research professor in electrical and computer engineering at the State University of New York at Binghamton, is approaching the fraud problem from the other side. She is trying to figure out who took the digital picture in the first place.

Just like the rifling in a gun barrel leaves a distinctive pattern on the bullets it fires, a digital camera has a signature of sorts. Today's digit

More About Investigating Digital Images

[rpiquepa]

I wrote about this technology a while ago, in "True or False? Investigating Digital Images." A keypoint is that the Dartmouth College team thinks that their technology, or a similar one, will soon be incorporated in the U.S. legal system to authenticate images. At the above link to my blog, you'll also find an analysis of a forged image and more references, including the full research paper published by the IEEE Transactions on Signal Processing journal.

Re:More About Investigating Digital Images

[TubeSteak]

The NYT article talked about a porn case where the prosecution couldn't prove the images were orignal & not fake... If the method of determining validity involves analyzing patterns etc. what's to keep someone from writing a program that will randomly change 0's & 1's? If this program doesn't significantly deteriorate/damage the original image, it'll look fine, yet it will also be detected as 'forged'. Once that happens, you won't be able to authenticate the image, nor conclusively declare it a forgery.

I realize it isn't as simple as flipping 0's & 1's but you get the general picture.

good background and intro, little details

[randyest]

Farid and his students have built a statistical model that captures the mathematical regularities inherent in natural images. Because these statistics fundamentally change when images are altered, the model can be used to detect digital tampering.

That's pretty much all the detail on the method to detect image altering. Seems reasonable, but:

1) How many real photos deviate how far from the statistical "norm" (i.e., how likely are false positives when checking for alteration?)

2) How long before there are tools that can inject the proper (expected) statistical characteristics into a faked image?

These are not addressed in the article. Anyone have more info?

Re:good background and intro, little details

[Anonymous Coward]

RTFP. 0.5% false-positives on their training data, ~1.5% on their test data... More to the point, the process is (of course) susceptible to certain kinds of manipulations... but it does really well with natural phenomena, even ones like 'strange lighting.' It really is picking up on statistical regularities that result from actually taking a photo (no matter what it is of) vs. those that come from, say, manipulating pixels in photoshop in a mathematical (that is, regular) way, no matter how subtle to the human eye.

reverse-engineering?

[chachob]

perhaps the technique could be reverse-engineered to allow the forgers to know whether or not their images can be detected as forgeries, and use this information to enhance their forging techniques to evade the detection tools...

Time for a Genetic Algorithm?

[sameb]

If there is an algorithm that can detect whether or not a photograph is forged, wouldn't it be possible to have another 'competing' algorithm that randomly altered bits and used the detection-algorithm as its success scale? (The better it becomes at not being detected, the better the genetic algorithm is doing.) Seems that that'd work fairly well, and would apply to lots of other technologies that require seamless photograph overlays.

Re:What kind of digitized photos does this work on

[blonde rser]

The NY Times article deals with this directly.

But Professor Farid said that for now the technique does not work as well with files created in JPEG, the compressed picture format most commonly used online. As the size of a JPEG file shrinks, the correlations between pixels become much less obvious. "At 90 percent quality, it falls apart very quickly," Professor Farid noted.

So good point. That does seem to be a problem. The NY Times article has more details than the other; it is worth reading.

don't believe the parent post since...

[John Harrison]

it's a trap!

and from the obvious paranoid side...

[zogger]

... they want to be able to pass off their "intelligence" photos as the real mc coy easier, so as to not get busted when they release crap, like the phony fat osama bin laden video(wicked fake) and the (possibly) berg beheading. this technology would help them to establish bonafides with the offical forgeries. We are *this* close to a running man scenario here with them being able to frame people or to alter public opinion with phony video and pictures. If they can create one and have it slip through the checking algorithms, then they are home free.

On the other hand, it would be nice to go back and look at a lot of older photos to see what's what with them now.

Lately there's a smidgen of controversy over some of the mars photos, this would be a great place to use the technique.

Re:What kind of digitized photos does this work on

[aka-ed]

This distinction is important, as it seems unlikely for any means to emerge that will overcome these pixel-level distortions.

One wonders whether this will lead to a legal distinction between lossily compressed images and others. While audiophiles have long been ape for lossless compression, not as much a need has been felt for graphics. Where do lossless graphic compression efforts stand? Is this an area where a proprietary standard might lead to big $$$?

Re:What kind of digitized photos does this work on

[multiplexo]

Good point. I should have RTFAMA (Read the Fucking Article More Attentively). Of course someone is probably already working on a Photoshop plugin for "correct faked image distortions", which would be handy to have along with some other plugins such as "remove ex-significant other from picture", "reduce glassy-eyed drunken stare", and my all time number one request, "remove drunk friends standing around with dicks hanging out by your mouth when you're unconscious".

Re:What kind of digitized photos does this work on

[Johnathon_Dough]

I take high resolution TIFF images and "muck with them" every day. Every ad you have ever seen has been digitally manipulated, every video image you have seen. If I am supplied with two good source images, I can create an image that would pass just about any inspection. There are many tricks to get the "irregularities" into (and most times out of) an image. If I wanted to create a fake image, I would do multiple techniques, then "print" the image out to a transparency (slide), or a negative, and have a print made, then scan the print. How would that go through this guy's algorithim?

To me this strikes me as the same sort of "solution" as DRM is, sure it stops Joe Six-Pack from putting Britney Spears' head onto a porn stars body, but it will not stop anyone who knows what they are doing when it comes to digital image manipulation.

from the author

[Hany Farid]

In response to some of the posts on our work, we have developed a number of different techniques for detecting certain types of tampering. For those interested in technical details, please see:

sp04.html
ih04.html
sacv03.html

And, we have two new papers currently in review (abstracts are currently on-line, and preprints will be available soon):

sp05a.html
sp05b.html

Some of these techniques work, as some have pointed out, only on high-quality jpeg or uncompressed images, while others work on lower-quality images. We are only in the early stages of development, and are currently working to extend some of these ideas to low-quality jpeg and gif images (though this will likely be a harder problem given that the compression artifacts will overwhelm any statistical perturbation resulting from tampering). One outcome of this may be that a legal standard is set that enforces images brought into a court of law to be of a certain resolution and compression quality.

I will be the first to admit that each of the techniques that we have developed can be reverse-engineered, though doing so is more difficult for some techniques than others. It is our hope, however, that as we and others continue to develop more techniques it will become increasingly more difficult (though never impossible) to simultaneously foil each of the detection tools.

Re:What kind of digitized photos does this work on

[rgmoore]

I strongly suspect that the solution will be some sort of hardware image signing, rather than after-the-fact examination. Canon already offers a Data Verification Kit for their superb EOS 1-DS digital SLR. They don't give too many details, but my guess is that they can attach a cryptographically signed hash of the image data into the file header so that it's possible to confirm the integrity of the data later. Since the EOS 1-Ds can only save data in raw and JPEG formats, and since this doesn't make sense for raw data (which has to be processed to be turned into a viewable image) it seems likely that they have this working with JPEGs.

The whole thing's a fraud...

[MoeDrippins]

...or the guy faked his own photo for the article.

C'mon now. math geek... handsome... math geek... handsome...

Sorry, I'm not buyin' it.

Doesn't work on .jpg's

[dpbsmith]

The New York Times article actually says something about the methods used. It basically works by looking at the kinds of operations that need to be performed when interpolating between pixels in manipulations such as changes in size, rotation, etc.

And, "Professor Farid said that for now the technique does not work as well with files created in JPEG, the compressed picture format most commonly used online. As the size of a JPEG file shrinks, the correlations between pixels become much less obvious. 'At 90 percent quality, it falls apart very quickly," Professor Farid noted.'"