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Video Services May Use Artificial Intelligence to Crack Down on Password Sharing

Still using your ex-roommates cable credentials to watch “Game of Thrones?” That may soon be getting a lot harder, thanks to new efforts to crack down on password sharing for pay TV and online video services. One of these efforts, launched by London-based Synamedia ahead of next week’s Consumer Electronics Show (CES), even uses artificial intelligence to uncover notorious password sharers.

Credentials Sharing Insight, as the new service is being called, targets both casual password sharing as well as criminal enterprises looking to resell pay TV login information. However, the focus clearly is on friends and family taking their generosity a bit too far, explained Symanedia chief product officer Jean-Marc Racine in an interview with Variety this week.

“The way you secure OTT is evolving,” said Racine. Previously, TV operators largely relied on secure devices, including locked-down set-top boxes and smart cards to decrypt satellite TV. These days, everything is moving to streaming, and operators are looking to make things as simple as possible for consumers. The flip side of that move to convenience is a lack of control, he argued. “Passwords are easy to share.”

And while TV operators in the past downplayed password sharing, claiming that it was just as much promotion, there’s a lot more caution about the topic these days. Parks Associates recently estimated that the industry could lose as much as $9.9B due to password sharing by 2021.

Most services have tried to curtail password sharing by limiting the number of simultaneous streams, with little else to go by to identify abuse. “Today, you are in the dark,” he said.

Synamedia’s solution on the other hand digs through lots of data to cluster users based on their streaming behavior. This can include user’s physical location (someone streaming from both coasts at the same time) as well as general usage patterns (someone streaming 24/7).

The company can even take a look at the specific content streamed by a user to identify unusual patterns. Based on these clues, Synamedia trains models to score users on a scale of 1 to 10, indicating whether they are likely sharing their passwords or not.

What the streaming service ultimately does with likely offenders is up to each company, said Racine. He suggested that the response doesn’t have to be punitive. Instead, companies could target password sharers with up-sell options for tiers with additional simultaneous streams. Services could also target users of shared passwords with specific messaging to convince them to pay up, or restrict access to the most popular content.

Whatever the response, Racine cautioned that it was important to dig into the data, and not jump the gun on users who may simply use the same account within their immediate family — something that is widely seen as acceptable. “You don’t want to have false positives,” he said.

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