Detecting Faked Photographs Gets Easier 258
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.
Self Defeating (Score:5, Insightful)
Just a thought... (Score:5, Insightful)
I wonder if they've considered the potential applications in image compression?
What kind of digitized photos does this work on? (Score:5, Insightful)
While this might not be a problem for gross manipulations (the faked John Kerry/Jane Fonda photo [sfgate.com] 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.
The unfortunate thing (Score:5, Insightful)
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 [dartmouth.edu] a paper covering the fakeness-detection algorithm. I hope the full algorithm will be presented to the academic community.
It will improve the fakes (Score:3, Insightful)
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? (Score:3, Insightful)
Re:Seamless Math Next? (Score:4, Insightful)
You, sir, have balls!
good background and intro, little details (Score:3, Insightful)
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:Seamless Math Next? (Score:5, Insightful)
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:
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? (Score:4, Insightful)
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:What kind of digitized photos does this work on (Score:3, Insightful)
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.
Re:More About Investigating Digital Images (Score:2, Insightful)
I realize it isn't as simple as flipping 0's & 1's but you get the general picture.
Re:Seamless Math Next? (Score:5, Insightful)
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? (Score:4, Insightful)
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? (Score:4, Insightful)
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 [snopes.com] together. This type of thing was possible before, but it was much, much more difficult and much less common.