The Intricacies of Face Liveness Detection in Facial Recognition
In a world where people search for convenience and ease when it comes to all aspects of life, it is no surprise that identification and authentication need to be fast as well. But the caveat is that when it comes to face recognition, speed can also mean less security.
This is where Face Liveness Detection as a concept and as a technology comes in. This new technology aims to make the increasingly common and fast method of biometric authentication which is face recognition more secure.
So, let’s talk about this technology and what it entails in today’s blog.
Facial Recognition vs Facial Liveness Detection
First, it would be a good idea to explain what the difference is between a simple face recognition process and facial liveness detection.
Face Recognition
Face recognition is simply the process through which an automated system scans an input face, checks it against a database of pre-approved faces, and then either approves or denies access to some system or interface.
For this purpose, it usually scans the different biometric ‘traits’ of your face, like your eyes, nose shapes, lips, and so on. It compares it to see if it matches one of the faces in its database, and if so, approves it.
Facial Liveness Detection
As with all other kinds of security measures, people are out there trying to trick these systems. Many people use different mechanisms like 2d images or face masks to emulate a real face and gain access to secure systems.
This is where face liveness comes in. This technology attempts to detect whether there is an actual, live human being present that is attempting to gain access to the system, or if a spoofing attempt is being made. In this way, it tries to make facial authentication more secure.
How Does Liveness Detection Work?
In a world where ‘remote’ authentication (like accessing apps on your phone sitting at home) is exceedingly common, having a mechanism for online liveness detection becomes extremely important.
How this piece of technology attempts to add a much-needed layer of security to the authentication process is that it not only detects facial features on a 2D plane but adds an additional layer of depth perception to it. By doing this it is able to capture and measure additional parameters that normal 2D image recreations are not capable of.
By capturing this depth-sensitive information, it creates a 3D map of your face that contains additional information like face curvature, distance between the eyes, and so on. This additional information is what stops someone from using a picture or something along those lines from imitating your face. This is why this technology is also referred to as 3D liveness detection.
Types of Facial Liveness Detection
Facial Liveness detection or 3D liveness detection is divided into two major kinds, based on the mechanism on which they work:
- Active Liveness Detection
- Passive Liveness Detection
1) Active Liveness Detection
Active liveness, as implied by the name, is a more active and involved, user-participatory process of identifying liveness. This kind of authentication prompts the user to perform some sort of facial action to identify if there is an actual person present. This can involve turning your head, smiling at the camera, and so on.
The system then analyzes the response from the user to these ‘challenges’, as they are known. It attempts to verify whether the movements seem natural and are indicative of actual human movement, rather than some form of video.
This kind of face liveness is somewhat more spoofing and imitation proof, as it involves active involvement. But it also does mean that it takes slightly longer for each authentication attempt to go through compared to its counterpart.
2) Passive Liveness Detection
Passive Liveness is a more seamless mechanism of facial liveness detection that does not require any manual participation from the user. This mechanism attempts to detect liveness from the input by detecting subtle facial movements that are natural in human beings. These can include things like blinking, skin texture scrunching, and so on.
This kind of detection can create a much faster facial recognition process, which generally tends to be relatively unobtrusive. But it does mean that it is slightly less secure, as there is no special input required.
The Concept of Hybrid Liveness Detection
The best liveness checking systems combine both active and passive detection. In this mechanism, the system initially attempts a passive liveness check. If it detects any irregularities, it then asks for an active liveness check from the user. This creates the most secure authentication system for facial detection.
Closing Thoughts
Detecting liveness during a facial biometric authentication process has become an extremely important mechanism in a world where these authentication tools are used to access sensitive information and systems. Since both Passive and Active Liveness detection have unique benefits to offer, a system that combines both to create a hybrid system may be the best authentication solution to use.