Feb. 2, 2021
As face authentication systems continue to improve, their use is becoming more and more widespread, from catching your next flight to the smartphone in your pocket. According to a report by the National Institute for Standards and Technology (NIST), the best face authentication algorithms now have an error rate of less than 0.2 percent, far better than human performance. However, face authentication technology on its own isn’t foolproof. In order to thwart malicious actors and bolster security, many organizations have taken to using face authentication with liveness detection. But what is liveness detection exactly, and how does liveness detection for facial authentication work?
“Liveness detection” refers to an AI system’s ability to distinguish between a live person and a false representation of that person. The task of liveness detection can be used for any biometric system, including face authentication, fingerprint scanning, iris scanning, speech recognition, etc. The possible forms of liveness detection for facial authentication include:
The term “liveness” was coined by computer science professor Dorothy E. Denning in her 2001 article “Why I Love Biometrics,” which is the source of the well-known quote “A good biometrics system should not depend on secrecy.” Denning argued that in order to be considered truly secure, face authentication software and other biometrics systems can’t just depend on hiding their inner operations—instead, they need to be truly robust to external attacks.
There are multiple possible ways that an attacker might try to counteract a face authentication system:
These methods are collectively known as a “presentation attack.” Liveness detection is the task of identifying these attacks and differentiating them from real users’ attempts to access the system, allowing legitimate users to continue to enjoy a fluid, uninterrupted experience.
There are two types of liveness detection methods, “active” and “passive”:
Active liveness detection methods should generally be supplemented by passive liveness detection in order to provide a high degree of confidence in the security of a face authentication system. Some of the forms of passive liveness detection include:
Face authentication with liveness detection is useful in a wide range of contexts and industries. Below are just a few examples:
Chooch’s facial authentication with liveness detection solution makes it easy for organizations of all sizes and industries to build rock-solid face authentication into their workflows. With extremely high accuracy and lightning-fast response times, Chooch’s facial authentication AI is a robust, mature solution for your needs and objectives. Get in touch with our team today for a chat about how we can help.