FaceShield launches to protect your digital facial data and privacy online

Each time you upload a photo of yourself online, your personal data – including age, ethnicity, gender and more – is subject to exploitation by third-party companies without your consent. FaceShield launches to protect your online identity and privacy to reduce the chance of online facial detection.

The free solution is as simple as uploading your image into FaceShield’s platform, which applies a filter of your choice to break face detectors. When the photo is uploaded, FaceShield’s algorithm generates “noise” on the photo to jam facial detection technology.

Through artificial intelligence, FaceShield applies noise to common areas of the photo that face detectors recognize, including the eyes, nose or jaw. The result of this noise is a shielded version that fools face detectors.

“While the general population is becoming more aware of online privacy and security issues, the vast majority is not aware that their facial data is being mined to create digital profiles for a variety of uses by third parties, which is a huge personal privacy violation,” said Joey Bose, Founder and President of FaceShield.

“We discovered that we could misguide a face detector into failure through advanced algorithms and technology that we’ve turned into a simple service for everyone to protect their identity online. The reality is people want to steal your data – and you need to protect it if you don’t want it to land in the wrong hands.”

The FaceShield demo on the website offers three different filters for your photos, each of which provide a different level of image alteration and protection. The Subtle option uses a filter that keeps the image as identical as possible to the original, but has the capability of breaking certain face detectors. The Medium and Intense filters increase the noticeability of the changes to the image, but break many more detectors.

FaceShield is accessible via desktop and mobile browser, ensuring ease of access. The company is funded by M2 Ventures and was created by a University of Toronto graduate student.

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