Questions? Feedback? powered by Olark live chat software

Lip Reading Technology May One Day Replace Traditional Typed Passwords

There’s a new technology being developed by researchers at Hong Kong Baptist University (HKBU) that stands to be a game-changer. Dubbed “lip password,” the new tech utilizes machine learning to recognize lip motion, shape and texture for each user when you speak your password.

Of significance, your voice has nothing to do with the password you set, it is entirely based on the movement of your lips. This matters because while a voice print would be difficult to mimic, it would not be impossible, given time and the right tools. The precise movement and shape of your lips would be virtually impossible for a hacker to duplicate, and the system would be even more robust if paired with facial recognition software.

The new tech is important in another way, too. One of the key drawbacks to current biometic password schemes, the two most common being retinal and fingerprint, is that they cannot be changed. If your fingerprints or retinal scans are ever hacked and released, there’s no way for you to “change your password.”

That’s not the case here. Simply speak a different word, and it’s done. Once testing has been completed and the new system is rolled out, it will give you the best of both worlds. The more robust security comes with biometric technology coupled with the flexibility and ease of use of current text-based passwords, including the ability to change them when and as needed.

Research and testing are ongoing, but the scientists applied for and got a patent on the technology in 2015. They expect that it will be ready for rollout later this year. Initial plans call for it to be deployed to the financial sector first, with other industries to follow after a trial period.

It may not be an ironclad, hack-proof system, but the early indications are that it’s the most robust password protection scheme we’ve seen to date, and that is good news indeed.

Used with permission from Article Aggregator