D-IDs tech protects your privacy by confounding face recognition algorithms

D-IDs founders Eliran Kuta, Gil Perry, and Sella Blondheim

Unless you literally wear a mask all the time, it is almost impossible to completely avoid cameras and face recognition technology. Not only is this a privacy concern, but it also presents a potential liability for companies that need to protect personal data. D-ID, a startup currently taking part in Y Combinator, wants to solve the problem with tools that process images to make them unrecognizable to face recognition algorithms, but still look similar to the original picture.

D-ID (its name stands for de-identification) was founded last year by CEO Gil Perry, COO Sella Blondheim, and CTO Eliran Kuta. Perry and Blondheim met when both were in the Israeli Special Forces about a decade ago, while Kuta served in the Israeli Intelligence Corps. At that time, photo-sharing on social media was relatively new, but they already needed to be mindful of face recognition technology.

We couldnt share our photos and profiles over the web because of sensitive positions. Even after we finished our service, we couldnt share our photos when we traveled in South America, Perry says. We felt bad because we are very social and everyone was sharing photos, but we couldnt.

Perry and Blondheim realized that people in the security industry were also forbidden from sharing photos online. They started brainstorming ideas to protect pictures from face recognition tech and came up with a basic algorithm. After an interlude of a few years, during which each of them worked on separate startups, they regrouped, added Kuta to their team, and launched D-ID.

Finding a way to deal with face recognition technology has become even more imperative. ATMs that use face recognition technology have already been deployed in Macau and are being tested by border control agencies in several countries. In China, its even been used to identify jaywalkers.

We started thinking about it when only people who worked in security or the government were very aware of face recognition technology, says Perry. Now everyone needs to be aware of it. Streets today are covered by cameras, we all carry smartphones. We are being photographed all the time. When you combine all the cameras and face recognition technology, privacy is actually gone.

The growth of D-ID will also be driven by new data privacy regulations like the European Unions General Data Protection Regulation (GDPR), which will become enforceable in May 2018 and require companies to guard personal data, including biometric data, more stringently or risk heavy fines. D-ID claims that its technology is designed to be difficult for artificial intelligence to overcome. Perry declined to go into detail about how the startups algorithms accomplish that, but said its goal is to be the standard of image protection, protecting every photo containing biometric data that is shared online.

D-ID serves three verticals: companies that need to protect images of their employees or customers, health management organizations, and government and security agencies that want to secure biometric data. It will launch a pilot program with cloud-based image management service Cloudinary to protect more than 14 billion media assets, Perry says.

Other companies that are developing ways to protect data from face recognition tech include ones that specialize in helping organizations comply with privacy regulations or offer data protection on a SaaS basis. Many of their tools work by making faces completely unrecognizable, but Perry says D-ID differentiates because their changes are much less detectable as possible, at least to the human eye. This element means that D-IDs tech can appeal to individuals who just want to protect photos they put online. Perry says a consumer app may be released if there is enough demand. D-IDs founders also say they welcome more competition because that means more companies are finding ways to help people protect their personal data.

Its an important point in time right now, with the progress of deep learning and every place being covered by cameras and regulators understand that, Perry says. More competitors are going to come and thats a good thing. we need to move fast in order to make an impact and we want to make as large an impact as possible in order to restore and protect privacy.

Read more: https://techcrunch.com/2017/07/20/d-ids-tech-protects-your-privacy-by-confounding-face-recognition-algorithms/

TrueFace.AI is here to catch the facial recognition tricksters

TrueFace.AI knows if it's looking at a real face or just a photo of one.
Image: ian waldie/Getty Images

Facial recognition technology is more prevalent than ever before. It’s being used to identify people in airports, put a stop to child sex trafficking, and shame jaywalkers.

But the technology isn’t perfect. One major flaw: It sometimes can’t tell the difference between a living person’s face and a photo of that person held up in front of a scanner.

TrueFace.AI facial recognition is trying to fix that flaw. Launched on Product Hunt in June, it’s meant to detect “picture attacks.”

The company originally created Chui in 2014 to work with customized smart homes. Then they realized clients were using it more for security purposes, and TrueFace.AI was born.

Shaun Moore, one of the creators of TrueFace.AI, gave us some more insight into the technology.

“We saw an opportunity to expand our reach further and support use cases from ATM identity verification to access control for data centers,” said Moore. “The only way we could reach scale across industries would be by stripping out the core tech and building a platform that allows anyone to use the technology we developed.”

“We knew we had to focus on spoof detection and how we could lower false positives.”

TrueFace.AI can detect when a face or multiple faces are present in a frame and get 68 raw points for facial recognition. But its more unique feature is spoof detection, which can tell real faces from photos.

“While working on our hardware, we tested and used every major facial recognition provider. We believe that doing that (testing every solution available) and applying facial recognition to a very hard use case, like access control and the smart home, allowed us to make a better, more applicable solution,” said Moore. “All of these steps led us to understand how we could effectively deploy technology like ours in a commercial environment.”

They made their final product by using deep learning. They trained classifiers with thousands of attack examples they collected over the years, and liked the results.

A “freemium” package is available to encourage the development community that helped TrueFace.AI come up with a solution. Beyond that, the Startup Package is $99 per month while the Scale Package is $199 per month. An Enterprise Plan is available via a custom agreement with TrueFace.AI.

While Moore couldn’t divulge exactly which companies are using the technology, he did say some of them are in the banking, telecommunications, and health care industries.

It’s a service that could become increasingly valuable as companies turn to facial recognition technology.

Read more: http://mashable.com/2017/07/07/trueface-ai-facial-recognition-photo-attack-detection/