Introduction to Paravision Liveness

As businesses and consumers increasingly turn to online services, ensuring the identity of users becomes more critical than ever. This is especially true in areas such as financial services, digital onboarding, and secure access to sensitive information. Verifying that a user is indeed who they claim to be poses a new set of challenges in the digital world, where face-to-face interaction is no longer possible. Liveness detection–also called Presentation Attack Detection (PAD) or anti-spoofing–is a necessary counterpart to face matching in remote or unattended applications, where fraudulent attacks such as presenting a photo, video, or mask in the place of a real face can undermine the trust that digital services rely on.

In this white paper, we explore Paravision Liveness 2.0, discussing how it works, the technology behind its high accuracy, and its advantages. We will also address critical considerations, such as the benefit of liveness using 2D/RGB imaging, the role of different camera types, and the distinctions between active and passive liveness detection.