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Blurring Images Not So Secure
An anonymous reader writes "Dheera Venkatraman explains in a webpage how an attacker might be able to extract personal information such as check or credit card numbers, from images blurred with a mosaic effect, potentially exposing the data behind hundreds of images of blurred checks found online, and provides a ficticious example.
While much needs to be developed to apply such an algorithm to real photographic images, he offers a simple, yet obvious solution: cover up the sensitive information, don't blur it."
Will this work on Japanese porn too? My friend wants to know.
While much needs to be developed to apply such an algorithm to real photographic images, he offers a simple, yet obvious solution: cover up the sensitive information, don't blur it."
And please, when you cover the information with black bars, use Adobe Acrobat. (this solution brought to you by the CIA)
Push Button, Receive Bacon
Squinting your eyes also works.
damn right. I see this happening on CSI all the time, the licence plate, blurred, reflected in a window, with someone standing in front of it.. just 'clean up the image', and bobs your uncle - one licence plate revealed clear as day. :)
You do realise that an algorithm to "un-blur" a blurred image is a total waste of time, right? There's no way for the algorithm to know how many times and in what various directions I blured the image - or if I added/deleted text before blurring. It's like a virus for Linux.. no one writes it because it's a waste of time. Leave it to slashdot to post bullshit.
Anytime I post a picture, such as a car with a license plate, I BLANK out the numbers/letters with three colors, a block of white, then a block of silver, then a block of black. Not layers, just the colors.
An unclassified report was released with information blacked out to make it unclassified. The problem is that whatever software was used to produce the PDF with classified information hidden had only applied a layer which was easily removed.
People who do not understand the technology they are working with should not have this kind of release authority. And that's the hard part--the higher up you are in the food chain, the less likely you are to understand the new tools your organization is working with.
There are very few users in government who could not do their jobs just fine using Windows 3.11, WordStar 3.x and an e-mail client on a fast but simple machine.
Slaved as the government is to Microsoft's development cycle, however, the government will always be at the cutting edge of compromised.
Don't trust anyone under thirty.
While I acknowledge knowning little about different blurring algorithms could someone enlight a bit how much of "unblurring" can be done? I realize there are some "sharpen" filters in Photoshop and Gimp but AFAIK they all seem to be based on highlighting edges or something like that.
As in the TFA, the Bill Gates picture has a small part of it blurred (his face). Could it be possible to calcute all the possible variations that give the same bitmap as the original when filtered with gaussian blur? What I glanced from gaussian blur page the group including all the possible solutions has to be finite, I guess, while being very huge..
This combined with a monkey (or bored computer user) could "help" refine the patter by selecting the most likely variation until the user is satisfied. Or is this something for which there already exists programs?
not always true. while it's reasonably good today, some day in the future, if we have 16-bit color channel depth ever become a standard (a 16-bit tiff for example), there will be enough data maintained at the edges of the blurred region to reconstruct the data. all you have to do is FFT the region, divide by a gaussian, inverse FFT, then keep repeating for different gaussians - this will basically divide out the system function used for blurring. 8-bit channels of today don't quite make it practical resolution-wise, but just a heads up so you don't get a false sense of security.
He basically points out that a blurred mosaic amounts to a form of inexact hash function. While irreversable, if you have a small enough input space, you can exhaustively hash all possible candidates and pick the one(s) that best match the target.
Interestingly enough, while he points out that most financial account numbers contain a degree of error detection and correction, he chooses to use that to reduce the match set, rather than the candidate set. I suppose this would matter if you wanted to prove a hypothesis (if the best match yields a valid number, you have a p=[valid/total]), but if you just want to steal someone's account info, you'd do better to reduce your processing time and just try the best few results in order.
and what is wrong with saying "i agree" to the article. this is a public forum for people to voice opinions, if you think that is wrong, just set the widget to show comments rated +5.
Why UNIX?
The whole point of the article is that blurring and pixelating beyond recognition isn't enough. You don't need to see the original numbers, you just have to find numbers that blur to a similar blob. It's a dictionary attack with blur as a hash function.
This is a kind of maximum entropy method, like the unsharp mask in image processing. Basically, if you know the blurring (convolving) function, you can reverse it. There are more sophisticated algorithms for cases where the blurring function is unknown, based on certain regularities; for example motion blur has a fixed direction and magnitude.
Escher was the first MC and Giger invented the HR department.
In the real world, data is imperfect and noisy, so the article is thus far correct. What is not correct is simply to pick the data with the nearest match, because it's a best match to the noise also. Maximum entropy is one algorithm which gives you a probabilistic answer, i.e. "the chances that this particular combination is the right one is [whatever] percent". You then pick the most likely one. Astronomers use this technique all the time for removing the blur and diffraction on their images. I personally use it regularly for nuclear spectroscopy, and it's absolutely solid if you use it carefully.
This message was scanned by European governments and contains no terrorism.
This is precisely why I hand write all my checks with a sharpe marker, here's an Example.
Wanna fight ? Bend over, stick your head up your ass, and fight for air.
Daniel Cohen-Or manages something I consider far more interesting. Take for instance this PDF about image reconstruction.
There's quite a few more impressive papers on his page, for those interested in graphics.
Indeed!
You're new here, aren't you?
In a lot of advanced image processing where you want to upscale an image, you can actually use a wavelet-based scaling technique that recovers amazing amounts of detail. In most digital TVs these days, they use a two-dimensional polyphase finite impulse response filter tuned for a certain degree of Gibbs phenomenon (ringing around harder edges) versus detail loss. But this has its limits, and it doesn't intelligently reconstruct the image details. In addition, it's notoriously difficult to tune properly for all content.
In contrast, wavelet based scaling can actually reconstruct phenomenal amounts of detail from a degraded image. For digital TV applications where you have DVDs or standard definition content displayed on a high-definition fixed-resolution display, wavelet-based scaling can actually make real details re-emerge where they weren't there before. The bottom line explanation is understanding and interpreting the influence of adjacent pixels with a minimum of error as the article's author demonstrates (although, as the parent post explains, he's going about it in a convoluted way). I've actually seen the preliminary results that some engineers had shown me that makes it look like something a government agency would use to enhance satellite or surveillance camera images. It makes DVDs look almost exactly like HD-DVD or Blu-Ray HD content. In fact, I expressed my concern that this scaling method could be used on digital TVs to actually "unmask" blurred or blocked faces on TV shows and introduce liability issues.
Nevertheless, it is possible to reconstruct a LOT of detail from blocked out or blurred faces or pretty much any content. Doing it in real time on HD resolution displays is a different matter altogether as it requires enormous computing power. But it is coming in the next 3-5 years. If you're really interesting in blocking out content on digital photos, use a solid black color over the part you don't want recognized.
So yes, I used an image against itself and designed it to work here. But the algorithem can surely be improved to work on real stuff. I don't have the time nor desire to improve this any further, though, because I'm not the one after your information.
Yeah, like: surely someone else can make it work - I've only described a fantasy in an article that'll work only under fabricated examples and circumstances and I don't want to put myself in a position of proving it unworkable in general use.
"It's time to take life by the cans." ~ Bender ("Bendin' in the Wind", ep. 3-13)
Ask the guys with talented girlfrends. ;)
Don't tell me to get a life. I'm a gamer; I have LOTS of lives!
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