As face biometrics continues to gain popularity with businesses and consumers alike, the need to adopt a better model of face verification is essential. In recent years, face recognition technology has provided a solution to security gaps that have been easily exploited by fraudsters. However, even with advancements in artificial intelligence, fraudsters are still finding ways to infiltrate customer signup and verification procedures.
As a way to ensure the integrity of face biometrics as a means of authentication and stop fraud, facial liveness has been introduced. But even with the innovation, the question of whether this new software is able to differentiate between identifying the right face and if the person is real is still a puzzle. This is where liveness detection comes in.
Deep Learning Algorithms
Liveness detection uses deep learning algorithms and computer vision to detect the presence of liveness in a person. This is a step ahead compared to the face verification that only uses facial images without proving whether the image is an inanimate person or a live person. Most facial verification technologies use the “active facial liveness” which requires users to move their devices around, turn their heads, or blink to confirm their authenticity.
This presents some challenges since fraudsters can easily use facial images or masks to trick systems. Because of these challenges, there was the need to come up with a surefire solution to ensure users’ safety. A second type of liveness detection was created known as “passive facial liveness”.
Passive vs Active Liveness Detection
In active liveness detection, the user is required to be present and do something to prove they are real. This slows down the authentication process, diminishing overall user experience and increases abandon rates. On the other hand, passive liveness detection has been designed to work without the need of the users to participate. Therefore, offering a hassle-free experience for the users.
Is Passive Liveness A Better Anti-Spoofing Solution Than Active Liveness?
One advantage of passive liveness has overactive liveness is that users are assured of protection without getting involved in the process. More companies are switching to passive liveness in order to keep their clients who do not have to take time from their busy schedules to verify their accounts every time they log in.
Other reasons why passive liveness is better than active liveness include:
- It lowers abandon rates significantly, keeping companies in business
- Enables a faster authentication process
- Requires less input from end-user
- Closes security gaps in facial biometric systems