Facial Recognition Is Everywhere – But So Are Tools To Defeat It

May 4, 2017

Apart from celebrities and high-profile fugitives, most people take for granted the ability to walk around in public without being identified by strangers, blissfully detached from their names and personal history. But more recently, this basic concept of public anonymity has been rapidly eroding.

Thanks to the rise of social media, ubiquitous cameras, internet-connected devices, and massive police facial recognition databases, more than half the U.S. adult population can now be near-instantly identified and tracked on the street simply by revealing their face. In response, privacy-minded engineers and activists have been fighting back with tech of their own.

“You can see a crumbling border between the cyber and physical worlds due to the spread of advanced sensors,” said Professor Isao Echizen during a recent talk at the International Workshop on Obfuscation at NYU Law School.

Before becoming a researcher at Japan’s National Institute of Informatics, Echizen spent a decade working in a research and development lab at Hitachi, where he designed copyright protection systems for the Japanese electronics giant. More recently, he’s been using his experience defending corporate intellectual property to defend people’s privacy.

In 2012, Echizen and his colleagues unveiled a prototype of the Privacy Visor, a bizarre-looking pair of glasses that defeats face detection systems by blasting camera sensors with beams of near-infrared light, which are invisible to the human eye.

The visor worked, but it wasn’t exactly subtle or flattering to wear. Commercial face detection algorithms have also evolved since then, and computer vision researchers have used advanced machine learning systems like artificial neural networks to successfully thwart various anti-face detection techniques — including Echizen’s prototype.

Now, after years of development, Echizen has unveiled an improved version of the Privacy Visor that doesn’t require power or use any electronics at all. Instead, the new model — which he officially released to market in March — uses repeating white patterns printed on a plastic transparency. The dense patterns reflect light back at the camera’s sensor, causing enough noise to prevent many algorithms from successfully detecting faces.

When I got my hands on one of Echizen’s Privacy Visors, I had almost no difficulty fooling the face detection schemes used by popular social media platforms. The puppy faces and other cute video filters provided by Snapchat’s face-detecting Lenses quickly disappeared after lowering the visor onto the center of my face — though it often needed a bit of adjustment. Facebook’s algorithm also didn’t detect any faces in uploaded photos of people wearing the visor from various angles and distances.

But as situations change and technology improves, experts say there’s no permanent “silver bullet” solution to the problem Echizen’s Privacy Visor is trying to solve. In a paper published last September, researchers at Cornell University built an artificial neural network that can de-obfuscate and match face images with up to 95 percent accuracy, even at extremely low resolutions.

“There’s no approach that ‘just works,’ or anything close to it,” Lujo Bauer, a researcher at Carnegie Mellon University who recently co-authored a paper detailing new methods of defeating facial recognition, told Vocativ.

That’s partly due to the old paradox of obfuscation: if you’re the only one actively trying to hide from surveillance technologies like facial recognition, you’re way more likely to stand out.

“In general, the more effective the approach, the more likely it is to be conspicuous to those nearby,” said Bauer. “A face recognition algorithm may not immediately identify you, but bystanders may gawk, and a human looking at a video feed would also likely notice that something suspicious is going on.”

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