Spoofing BioID Face Liveness Detection 2024 | 3D Silicon Mask | Anti-Spoofing Deepfake Detection

[@iliade_edaili]

The other day I checked with the face of a "baby reborn" doll. And latex masks, made up and with skin textures, pass easily through your system.

[@bioidgmbh]

Thanks for letting us know, we’re always interested in new spoofing instruments! We are regularly updating our neural networks, as deep learning based technologies are constantly evolving.

[@Truve-eee]

Lovely

[@bioidgmbh]

You can find our sample code for face #LivenessDetection on Github: github.com/BioID-GmbH/FaceLivenessDetection If you haven't, yet, you can also check out the BioID Playground to test our #liveness and #FacialRecognition implementations: www.bioid.com/playground/

[@bioidgmbh]

Your system can be spoofed! That's what we hear when someone injected a video into a system as a virtual camera attack. Well, not really! The spoofing target in that attack scenario was the application, and NOT our technology (our API and the algorithms performing the biometrics were not even touched). There is a major difference between application level attacks (need to be countered by a secure app, preventing any virtual camera access, for instance) and a presentation attack. The latter is exactly what BioID's liveness detection is aimed at and what is demonstrated in this video: It prevents any presentation attacks (fake biometrics presented to the camera), such as video replays, deepfakes presented on screens, 3D paper, silicon and other masks, etc. There is no question that an application level attack needs to be prevented, as well, to make identity verification secure. But, BioID does not build end-user applications, and instead supports their customers with reliable, ISO 30107-3 compliant PAD/liveness detection. When working with our customers we of course support and consult them concerning the construction of a secure app. Together, we join forces with our partners to prevent criminals from harming individuals' identities.