Washington, Oct 6 : An Indian origin scientist at the University of Buffalo is developing an automated system that would make detection of potential terrorists easier for law enforcement authorities.

The system would track faces, voices, bodies and other biometrics against scientifically tested behavioural indicators to provide a numerical likelihood that an individual is about to commit a terrorist act.

“The goal is to identify the perpetrator in a security setting before he or she has the chance to carry out the attack,” said Venu Govindaraju, Ph.D., professor of computer science and engineering in the UB School of Engineering and Applied Sciences.

Dr. Govindaraju said the focus is on “developing in real-time, an accurate baseline of indicators specific to an individual during extensive interrogations, while providing real-time clues during faster, routine security screenings”.

“We are developing a prototype that examines a video in a number of different security settings, automatically producing a single, integrated score of malfeasance likelihood,” said Dr. Govindaraju, a 1986 IIT Kharagpur computer science graduate.

Dr. Govindaraju said, recently the National Science Foundation awarded an 800,000 dollars grant to the project.

He said a key advantage of the UB system is that it incorporates machine-learning capabilities, which allows it to “learn” from its subjects during the course of a 20-minute interview.

Dr. Govindaraju said that’s critical, because behavioural science research has repeatedly demonstrated that many behavioural clues to deceit are person-specific.

“As soon as a new person comes in for an interrogation, our program will start tracking his or her behaviours, and start computing a baseline for that individual 'on the fly',” said Dr. Govindaraju.

Co-researcher Mark G. Frank, Ph.D., associate professor of communication in the UB College of Arts and Sciences, said the technology, however, precise, would not be a substitute for human judgment.

“No behaviour always guarantees that someone is lying, but behaviours do predict emotions or thinking and that can help the security officer decide who to watch more carefully,” said Dr. Frank.

“Individuals are often randomly screened at security checkpoints in airports or at border crossings. Random screening is fair, but is it effective? The question is, what do you base your decision on – a random selection, your gut reaction or science?

“We believe science is a better basis and we hope our system will provide that edge to security personnel,” he said.

Dr. Govindaraju said their system would avoid some of the pitfalls that hamper a human screener's effectiveness.

“Human screeners have fatigue and bias, but the machine does not blink,” he said. (ANI)