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As security becomes a hot topic in different industries, researching ways to improve the systems we have has become of the utmost importance. With the major data breaches that have happen in this year alone, businesses are looking for better ways to beef up their access control and security systems and stay one step ahead of data hackers. 

Robotic Hand Reaching Out

Biometric security is far ahead of the curve in terms of effective access control and identity authentication. Many businesses have already made the switch from pins and key card to biometric authentication or two factor authentication which biometrics included for their security needs. However, recently the idea of combining the learning abilities of artificial intelligence with biometric access control has come into play.  

AI powered biometrics as a security innovation has the potential to not only authenticate users based on their physiological characteristics, but also on contextual cues fro behavioural biometrics as well. Behavior biometrics measure and classify human activities. Things like voice inflection, keystroke dynamics, error patterns, stance and gait among many others. By including behavioral biometrics, it creates an additional level of security to be used in tandem with the user’s physical biometric information. In combining both the physical and behavior aspects of the user’s identity, there are less false authentications and users not exhibiting both aspects of the enrolled identity are prevented form entering. 

In traditional biometric systems, the information about each user is collected during the enrolment of the user and then is used to authenticated said user when they need access to the controlled area. By integrating AI with biometric security, these devices would be collecting behavioral biometrics each time the user authenticates their identity. In doing this, the biometric reader collects meta data on the unique characteristics of the user. And because this learning isn’t static, the device will be able to adapt to changes in the user’s behavior over time. 

While this all is interesting, why do we need this extra layer of security? Well if your biometric authentication system is able to not only carry out authentication, but also learn from contextual and situational cues, your whole security solution will be better for it. Drastic changes in behaviors, time and location of authentication and changes in interactions with the machines (more errors than usual when entering a pin for example) will be noted by AI Biometric devices. 

In these cases, depending on the programming, the device will deny access to the user or ask for additional verifications of their identity. Creating more steps in the authentication process when detecting anomalies in a user’s behavior could be the difference between a breach and a close call. 

We can already see the industry take steps towards this kind of innovation with biometric readers integrated with machine learning. Facial recognition devices like the Facestation 2, continuously collect data from users during authentication so that they can adapt to changes in the users faces over time. These types of functions are the first steps in biometrics becoming fully integrated with AI technology 

The future for biometric security is a bright one. These systems have the capability of delivering a more secured enterprise that protects the data of its users. While we might not have the technology yet, with the rate at which AI research is developing, it may arrive sooner than you think. Until then, make sure your biometric security system is on par with the industry’s leading edge and you’ll be ready for when it does.