4 ms·
That's right, successfully preventing spoofing attacks using 2D input is an extremely hard problem to solve. We've spent two years working on it. We published a
by emilxix 6y ago
That's right, successfully preventing spoofing attacks using 2D input is an extremely hard problem to solve. We've spent two years working on it. We published a high-level overview here - https://getxix.com/learn https://getxix.com/learn and plan to publish a deep-dive overview of the approach in the coming weeks.
For SSO, Entry can be added as SAML 2.0 Factor today. I agree if we would not have solved the spoofing problem, taking the Auth0-style route for native platforms is the way to go.
- wgjordan 6y agoRelevant quote from the linked overview: > Entry addresses the spoofing issue from 2D input by using an anti-spoofing algorithm that processes a sequence of images obtained from a single camera to build an accurate 3d face reconstruction based on facial key points. Additionally, it estimates the pixel distribution of the input image to detect attacks. Aggregation of both methods achieves high accuracy for detecting attacks on face recognition systems.
- carlosdp 6y agoWhat stops an attacker from spoofing the webcam with a looping video of the subject staring at a camera instead of a still image or holding up a picture?
- emilxix 6y agoSeveral layers of anti-spoofing. They detect mask-attacks, replay attacks (put the phone with video into the camera; highjack a webcam input and send a pre-recorded video faking to be real-time from zoom for example), and, of course, still images. Give it a try!
- pmiller2 6y agoWouldn’t you still be vulnerable to attack via a 3D printed or resin cast face (possibly suitably painted)?
- qbasic_forever 6y agoOr just tape a print out to a balloon.