Researchers at Russia’s Institute of Cyber Intelligence Systems at the National Research Nuclear University (MEPhI) led by Konstantin Kogos, have developed a system of continuous authentication for smartphones based on behavioral biometrics.
While password-based authentication makes up the bulk of mobile device security systems, many users consider it an inconvenience to constantly re-enter numbers or unlock patterns to access their devices. Fingerprint authentication, while popular, can be infiltrated by hackers using malicious apps to replicate device owners’ fingerprints and even adding their own fingerprint, thereby locking out the device owner.
Behavioral biometrics on a mobile device offers the owner continuous authentication and protection from hackers by monitoring the unique parameters of the owner’s device handling to determine if a handler is the device’s owner or someone else. The researchers explain that mobile device owners have unique manners in which they hold their device, interact with the touch screen, and use the device’s functions. These parameters would be subject to constant monitoring under a behavioral biometrics system. “Our scientific innovation is that for the first time ever, we used data analysis and machine learning technologies, as well as artificial neural networks, to monitor behavioral biometric characteristics in order to ensure the continuous authentication of the smartphone user. The sensitivity of sensors in today’s smartphones allows them to recognize the unique behavioral characteristics of each user and, based on the set of data collected from the touch screen and other sensors, to conduct high-accuracy authentication,” said Kogos.
Related Research Papers:
A Concept of Continuous User Authentication Based on Behavioral Biometrics
SegAuth: A Segment-based Approach to Behavioral Biometric Authentication