Biometric authentication is increasingly being incorporated into security applications. With that, significant attention is focused on both the quality and accuracy of biometric technology.
In order to promote public acceptance and support, along with the minimizing of security breaches and misidentification, a number of biometric systems now incorporate an additional layer of security. Liveness detection.
A breakdown of biometrics
How much do you know about biometrics? Biometrics are a security technology that make use of individual features each of us has. This could include our face, fingerprints, or retina. Biometrics are used in law enforcement, immigration, and also as a substitute for passwords, IDs and other types of personal identification.
Biometric authentication use compares current user biometrics to those that are already in the system they are using.
Facial recognition technology has seen great advancement leaps, with systems that can today detect even the smallest of changes in an individual’s features. A new hair color, facial hair, reading glasses and other partial facial obstructions are much less likely today to prevent the identification of the user. There has also been great progress on ensuring accurate identification in differing lighting settings, and with a variety of complexions.
With a dramatic decrease in false rejections and significant increase in accuracy improvement, there are still ways that savvy criminals can spoof these biometric markers.
Biometrics spoofing is the term used when individuals, typically criminals, use any kind of replication product or tool in order to trick the system into believing that they are someone else. Fingerprints alone are fairly easy to spoof, with countless movies and television shows demonstrating that adhesive tape or putty can defeat many systems. Photos, videos and even cleverly made masks and makeup have each been used as a tool to defeat many facial recognition systems.
These are documented weak spots in all biometric systems. As these types of identification technology are integrated with increasing frequency, these concerns are bound to impact the levels of confidence that users have in it.
Here’s where liveness detection comes in
Liveness detection is a handy security feature that can help to make sure that biological identifiers are from the specified user and not from someone trying to spoof the system. It is the ability of an automated system to detect that it is interfacing with an actual human who is physically there, and not an inanimate spoof image or a video.
What is liveness detection looking for? Lip or eye movement analysis, prompted motion, texture and reflection detection on video, zooming motion detection, and 3D depth analysis.
There are two types of liveness detection in use today.
- Passive liveness detection
- Active liveness detection
Passive liveness detection makes use of encoded algorithms that don’t require anything from the user as they detect spoofs.
Active liveness detection uses techniques where the user is asked to perform specific actions, like blinking or making a facial movement. This makes it more of a challenge and time-consuming for a fake user to spoof the system.
As an example, when you log into your banking app using facial recognition, it may use an active liveness detection system to ask you to blink while it scans your face. If the banking app uses passive liveness detection, it may scan your face to make sure that a real person is present, with the individual’s unique depth contours.
Liveness detection methods can take slightly longer to identify users, but they bring with them an increased safety measure that makes it worth it.
What does the future of liveness detection look like?
Biometrics have come a long way. With this have been great improvements in liveness detection. Advanced technologies are being put to good use to make sure that liveness detection is highly secure but also still highly efficient in order to avoid frustrating users.
In order to boost public opinion about biometric security methods, both anti-spoofing and liveness detection methods need to be improved. This means implementing accessible and accurate liveness detection that will offer the speed and exceed the security and accuracy of traditional biometric identification methods.