Liveness Detection Vs Facial Detection
While facial biometrics are quite impressive, liveness detection tops it all. Algorithms used in facial recognition have high accuracy when matching faces. However, they cannot differentiate between a face that is live and one that is not.
This has created a loophole for fraudsters to take advantage of. While it might not cause many problems in supervised areas, it is a big issue with remote authentication. Fraudsters use a variety of impersonation tools to trick face recognition systems.
Some of them include:
- Deep-Fake or Synthetic Videos – Here, fraudsters use a video or a photo of an individual to create a realistic version of them. They then use these images to bypass facial recognition.
- 3D Mask or Models – This involves creating 3D models that mimic the likeness of individuals that fraudsters intend to defraud.
- Video or Photo Attacks – In this attack, fraudsters get hold of your photo or video and use it to defraud you. They can get them from your social media accounts or via a google search.
To seal these loopholes, experts came up with a better solution.
Facial Liveness Detection
With all the shortcomings of facial recognition, liveness detection provides the solution. This system authenticates if an image is of a live person or not. No matter which device you are using, if it is camera-enabled, liveness detection will give accurate results. There are two types of facial liveness:
Active Facial Liveness
It is the most common option used today. Users are subjected to some tests so that the system can capture all their facial characteristics. This includes smiling, blinking, or turning your head.
Passive Facial Liveness
This type of facial liveness is elusive to fraudsters. It does not require certain actions such as smiling or blinking. These can be replicated in a deep fake. Instead, the system captures your facial traits in your natural form doing normal things.
For business owners who are value security, facial recognition with liveness detection is a perfect path to pursue. Whether it is passive or active, facial recognition is steps ahead of traditional biometrics.