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Google adapts YouTube's copyright-ID technology to combat child-porn



By Vivek Gangjee
01 May 2008 @ 3:35 pm IST


The fight against child pornography has received a new boost with an assisting technology designed by Google that helps to identify copyright-protected clips on its YouTube video-sharing site.
The fight against child pornography has received a new boost with an assisting technology designed by Google that helps to identify copyright-protected clips on its YouTube video-sharing site.
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The Google technology now enables NCMEC analysts to sift through more quickly and easily as the tools search NCMEC's systems sorting and identifying files that contain images of child pornography victims. The new video tools will also help in streamlining analysts' review of video snippets from files seized in child pornography cases.

Both Google and the NCMEC haven't revealed many details surrounding the new technology, which is not surprising given the sensitive nature of law enforcement investigations that go into child pornography and abuse cases.

However, Larry Magid, founder of SafeKids.com and an unpaid member of the NCMEC board of directors cited some examples that illustrate the power of Google's contribution.

"The software allows an analyst to highlight a pattern somewhere in an image. It could be a calendar on the wall, a logo on a T-shirt, a prominent tattoo or perhaps the pattern of the carpet. It then looks for that pattern in other images and when it finds a match or a likely match it presents those images to the analyst. In some cases it will analyze the entire image to look for matches or near matches," Magid said, emphasizing that with the software, the human analysts do not have to depend on memory to catch similar or unique characteristics between images any longer.

"Our analysts have been doing a tremendous job with their memory, but computers have much longer memories," Michelle Collins, executive director of Exploited Children Services at the NCMEC, said. She also said that while a human might not remember a pattern seen 4 million images ago, "the system should be still able to pick that up."

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