ImageWare Launches Selfie-based Anti-spoofing Solution

“It’s a frictionless selfie authentication solution, with no requirement of special actions from the user like blinking or smiling; and it’s designed to perform its anti-spoofing analysis entirely on a remote server, eliminating the need to install bulky AI software on the user’s smartphone.”

Bometrics News: ImageWare Launches Selfie-based Anti-spoofing Solution

ImageWare has announced a new liveness detection solution for its portfolio of biometric solutions.

Called “Biointellic”, the system is based on convolutional neural networks and machine learning, and is able to operate through a standard smartphone camera. The end user needs only to take a simple selfie, and Biointellic will guard against presentation attacks based on videos, masks, and so on.

It’s a frictionless selfie authentication solution, with no requirement of special actions from the user like blinking or smiling; and it’s designed to perform its anti-spoofing analysis entirely on a remote server, eliminating the need to install bulky AI software on the user’s smartphone. And ImageWare says that because the system has been built on Docker and Kubernetes container platforms, it’s highly scalable.

What’s more, the Biointellec solution is currently undergoing testing at the renowned iBeta lab to verify compliance against ISO 30107-3, the world’s preeminent standard for biometric Presentation Attack Detection.

In ImageWare’s last quarterly update, CEO Jim Miller pointed to a growing interest in biometric identity management technologies, which in turn is helping to promote interest in the company’s authentication platform. Alongside that trend is a growing interest in anti-spoofing solutions, since presentation attacks are an emerging and serious threat in response to the growth of biometric authentication; so ImageWare’s new Biointellec solution is a well-timed one.

July 31, 2019 – by Alex Perala

[Update: A previous version of this article incorrectly stated that Biointellic applies facial recognition; it has been updated to reflect the solution’s use of liveness detection exclusively.]