A research team at Binghamton University have formulated a biometric ID method called Cognitive Event-RElated Biometric REcognition (CEREBRE) for identifying a persons specific “brainprint.” Researchers documented brain activities of 50 subjects wearing an electroencephalograph (EEG) headset whilst viewing selected images from a set of 500.
The teams found that participants’ brains reacted uniquely to every image — enough so that a computer system that analysed the different reactions was able to identify each volunteer’s “brainprint” with 100 percent accuracy.
In their original brainprint study in 2015, published in Neurocomputing, the research team was able to identify one person out of a group of 32 by that person’s responses, with 97 percent accuracy. That study only used words. Switching to images made a huge difference.
It’s only a three-point difference, but going from 97 to 100 percent makes possible a reliable system for high-security situations, such as “ensuring the person going into the Pentagon or the nuclear launch bay is the right person,” said Assistant Professor of Psychology Sarah Laszlo. “You don’t want to be 97 percent accurate for that, you want to be 100 percent accurate.”
Laszlo says brain biometrics are appealing because they can be cancelled (meaning the person can simple do another EEG session) and cannot be imitated or stolen by malicious means, the way a finger or retina can (as in the movie Minority Report).
“If someone’s fingerprint is stolen, that person can’t just grow a new finger to replace the compromised fingerprint — the fingerprint for that person is compromised forever. Fingerprints are ‘non-cancellable.’ Brainprints, on the other hand, are potentially cancellable. So, in the unlikely event that attackers were actually able to steal a brainprint from an authorised user, the authorised user could then ‘reset’ their brainprint,” Laszlo explained.
Analysing “event-related potential” brain signals
The researchers found in their original study that the key to detecting differences in brain signals was to look at and analyse “event-related potential (ERP) brain signals recorded from each subject. ERPs are brain signals that are triggered by specific events (such as seeing a photo). Unlike EEG signals, ERPs are unique and happen over a period of a few milliseconds.
Read this article in full at: Kurzweil.Ai
Andrew Hatling/Binghamton University | The New Biometric — Brainprint