New cybersecurity system senses eye shape and muscle movement to provide more secure, reliable identity recognition and more.
While many of us rely on passwords to protect our identity, there’s more sophisticated identity recognition technology called biometrics that we could use. Security measures that use biometrics rely on a person’s unique characteristics and traits rather than on what that person can remember, such as a password. Ocular biometrics, in particular, relies on iris and retinal scanning.
With support from the National Science Foundation (NSF), computer scientist Oleg Komogortsev and a team at Texas State University are taking the technology a step further, making it even more secure, reliable and nearly impossible to fool.
They are developing a three-layered, multi-biometric approach that tracks the movement of the eye globe and its muscles, and monitors how and where a person’s brain focuses visual attention, in addition to scanning patterns in the iris. The iris is the colored part of the eye.
The team’s system essentially upgrades the security of existing iris recognition technology with nothing more than a software upgrade, and the benefits extend well beyond security. This technology can detect not only the identity of the person, but the state of the person, including the individual’s level of fatigue or stress. Komogortsev says it could even be used inside the helmets of football players to detect concussions.