Goljan Slides 
2009-02-21 - extension: rar - size: 41 MB
Goljan Slides
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Goljan 16-20 2008-12-31 - extension: rar - size: 43 MB
Goljan 16-20
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Video results for: goljanMore results from video 
Going Gonzo at a Rubik's Cube Competition http://www.dreamnotoftoday.com/
Rolling out of bed at the crack of noon, my phone was buzzing (More) http://www.dreamnotoftoday.com/
Rolling out of bed at the crack of noon, my phone was buzzing with untold excitement. Today was an assignment, one that required a sharp head and a courageous heart. The alarm said the San Francisco 2009 Rubik's Cube International Open had started two hours ago. That shit, shower and shave had to be dispensed with and dispensed with quick, for the day's quarry on the continuing hunt for the truly gonzo was known for one thing and one thing only: speed.
Featured in our coverage are true luminaries of the world of speed cubing with original gangsters Milek Goljan and Lars Petrus, international warlords Frank Morris and Dan Dzoan, as well as rising Bay Area speedcuber Jeremy Fleischman.
http://www.dreamnotoftoday.com/ (Less)
Digital Forensics at Binghamton University Research links digital images, cameras
Child pornographers will soon have a harder time escaping (More) Research links digital images, cameras
Child pornographers will soon have a harder time escaping prosecution thanks to a stunning new technology that can reliably link digital images to the camera with which they were taken, in much the same way that tell-tale scratches are used by forensic examiners to link bullets to the gun that fired them.
The defense in these kind of cases would often be that the images were not taken by this persons camera or that the images are not of real children, said Jessica Fridrich, associate professor of electrical and computer engineering. Sometimes child pornographers will even cut and paste an image of an adults head on the image of a child to try to avoid prosecution.
But if it can be shown that the original images were taken by the persons cell phone or camera, it becomes a much stronger case than if you just have a bunch of digital images that we all know are notoriously easy to manipulate.
Fridrich and two members of her Binghamton University research team Jan Lukas and Miroslav Goljan are coinventors of the new technique, which can also be used to detect forged images.
The three have applied for two patents related to their technique, which provides the most robust strategy for digital image forgery detection to date, even as it improves significantly on the accuracy of other approaches.
There are about six or seven forgery detection techniques in the literature, Fridrich said. And each one of them breaks at a certain point. You can always come up with a case where any particular technique including ours will not be applicable. So our technique is another tool for forensic examiners to use
an example of the noise the researchers believe to be unique to each digital camera.
in cases where they have the camera itself or multiple images taken by the same camera.
The nice part about this is that the reliability with which you can reach a decision about forgeries is orders of magnitude higher than anything ever built before.
Fridrichs technique is rooted in the discovery by her research group of this simple fact: Every original digital picture is overlaid by a weak noise-like pattern of pixel-to-pixel non-uniformity.
Although these patterns are invisible to the human eye, the unique reference pattern or fingerprint of any camera can be electronically extracted by analyzing a number of images taken by a single camera.
That means that as long as examiners have either the camera that took the image or multiple images they know were taken by the same camera, an algorithm developed by Fridrich and her co-inventors to extract and define the cameras unique pattern of pixel-to-pixel non-uniformity can be used to provide important information about the origins and authenticity of a single image.
The limitation of the technique is that it requires either the camera or multiple images taken by the same camera, and isnt informative if only a single image is available for analysis.
Like actual fingerprints, the digital noise in original images is stochastic in nature that is, it contains random variables which are inevitably created during the manufacturing process of the camera and its sensors. This virtually ensures that the noise imposed on the digital images from any particular camera will be consistent from one image to the next, even while it is distinctly different
Jessica Fridrich, associate professor of electrical and computer engineering, and two colleagues have developed a technique that can tie digital images
from the noise produced by any other camera even one of the same make and model.
In preliminary tests, Fridrichs lab analyzed 2,700 pictures taken by nine digital cameras and with 100 percent accuracy linked individual images with the camera that took them.
Now, we are focusing on analyzing the reliability and mathematically describing the algorithm, she added.
Fridrich, who specializes in all aspects of information hiding in digital imagery, including watermarking for authentication, tamper detection, self-embedding, robust watermarking, steganography and steganalysis, as well as forensic analysis of digital images, says it is the absence of the expected digital fingerprint in any portion of an image that provides the most conclusive evidence of image tampering. (Less)
Goljan High Yield 2009-11-11 - extension: rar - size: 38 MB
Goljan High Yield
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new goljan notes 
2009-11-10 - extension: pdf - size: 6 MB
new goljan notes
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new goljan notes 2009-11-04 - extension: pdf - size: 6 MB
new goljan notes
Hosted on: rapidshare.com
