OkayFace

Thanks to leapfrogging advancement in deep learning, the facial recognition API is quickly becoming mainstream. The vast availability of facial recognition API over cloud-based subscription, is making it almost utility-like now.

However, not all facial recognition APIs are born equal. Some may not be commercially available for on-premise deployment option when required, while some remain less commercially tested for varying skin tones, and most importantly – many commercially available options are not supported with highly secure liveness detection component.

OkayFace is applied to following use cases

Real-time Facial Sighting

Substitution to Password

Multi-factor Authentication

OkayFace is powered by facial verification algorithm that satisfies 0.000001 false match rate. This is further strengthen with liveness detection component that supports financial-grade anti-spoofing techniques.

Liveness detection (also known as anti-spoofing) is a process that should take place before facial recognition, in use cases that requires stringent verification of a person’s facial identity. It makes sure that the person (user/customer) you are interacting with, remotely over an app, is indeed a live person and not a photo or recorded screenplay. It prevents spoofing attacks.

The liveness detection technique offered is:

  • Passive liveness detection: Also known as non-interactive mode, or silent mode, this deep-learning-based technology only requires a single-frame portrait photo from live camera to determine if a face is live or otherwise.

Key Advantages

  • Prevent spoofing attack from printed photo, portrait displayed from screen, deepfake, animated talking head, and printed face mask with edges cut-out
  • Supports multi-channel UI, without dependency on native mobile app technology
  • Proven implementation that involved multi-ethnic population in Southeast Asia
  • Support and technical expertise in Southeast Asian timezone
  • Readily integrated with ID capture technology to support facial ID verification with various identity documents, such as passport, national identity card and driver’s license.
  • Presentation attack detection methods that adhere to ISO 30107-3 guidelines.

Facial verification technology tracks more than facial keypoints, with recorded accuracy of 99.50% or higher. 

Understand Spoofing Attacks in Facial ID Verification, and How Your Business can Prevent Them

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