A Silicon Valley start-up has licensed a University of Memphis (UM) authentication technology that analyzes environmental conditions such as noise or light to improve cybersecurity.
The technology is an adaptive, biometric multi-factor authentication system that leverages a machine-learning algorithm to choose the best mode of user authentication depending on environment and operating conditions.
According to inventor and UM researcher Dipankar Dasgupta, the technology would automatically choose not to use voice recognition in a loud environment such as a coffee shop, nor facial recognition in an environment with low lighting, in an effort to prevent hackers from compromising users.
The Silicon Valley start-up i2Chain licensed Dasgupta’s technology from the University of Memphis Research Foundation (UMRF) and plans to integrate it into a service for identity providers. Hai Trieu, director of tech transfer at UM, says i2Chain was chosen because it wanted to put the high-potential technology to good use, whereas a large corporation might license it simply to prevent it from turning into competition.
“We wanted to find a company who was capable,” says Trieu. “i2Chain happened to be very qualified. They could start something innovative and do something very different.”
Under the licensing agreement, UM will receive a percentage of revenues from sales of the technology. The university plans to funnel these earnings into future research and development projects.
Source: Biometric Update
