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Twitter To Implement Microsoft’s PhotoDNA System To Block Child Porn

The Guardian reported yesterday, in an exclusive from Twitter, that the social network will be introducing a tagging system to prevent child porn images being posted.

Unfortunately, the current Twitter ecosystem sees millions of child abuse pictures posted among the millions of tweets sent every day.

The system, which will use a Microsoft-developed industry standard called PhotoDNA, is to be implemented “later this year if possible.”

The news comes on the heels of UK Prime Minister David Cameron’s announcement of an initiative to tackle child pornography across the Internet, not just social networks.

Apparently PhotoDNA, which was developed in 2009, is already used to monitor images posted to Facebook (since 2011), Microsoft Skydrive, and Bing. And Google has used a similar technology to identify child abuse images online since 2008.

PhotoDNA works by producing a “hash,” a single number generated from the binary data of a picture or video, which is compared against known images of child abuse which have been flagged. PhotoDNA recognizes offending images even if they’ve been altered.

The complication in integrating the system into Twitter is the scale and speed of the network, as Del Harvey, senior director of Twitter’s Trust & Safety team, points out. And that’s not all. Harvey told the Guardian,

“You think ‘we’ll just delete the image’, but then you face the question of whether it’s hosted on a [Content Delivery Network]. In that case, how do you make sure it gets flushed out? What if there’s a backlog of requests for images to delete? You start to wonder if these things really have to be this complicated just to delete an image – and the answer turns out to be yes, it really does have to be this complicated.”

Despite the challenges, it’s a noble initiative. And a much-needed fortification of Twitter’s child protection measures, which the Child Exploitation and Online Protection Centre reported in 2012 to be lacking behind other social networks’.

(Padlock image via Shutterstock.)

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