Making 2FA More Secure
Two-factor authentication is not a new technology and many companies use social media apps to verify someone’s identity, but now the possibility integrating it into facial recognition can add an extra layer of security.
Two-factor authentication (often shortened to 2FA) provides a way of 'double checking' that you really are the person you are claiming to be when you're using online services, such as banking, email or social media. It is available on most of the major online services. Essentially, two-factor authentication is the process of confirming one’s identity through two different challenges, using something you already know, have, or contain.
In two-factor authentication, one test can be to fill in the username and password. The next challenge can be to verify the identity by tapping on a push notification, entering an OTP shared via email, text message, phone call, or other channels.
Now a team from Brigham Young University School of Mathematics (BYU) has built an algorithm that could possibly bring two-factor authentication to facial recognition technologies in everything from cell phones to surveillance systems with the use of facial motion.
The project started when the group researched facial motion and how it could be analysed. That evolved into seeing if students are paying attention in class and it eventually morphed into improved security for facial recognition with the use of facial motion. They developed a technology called Concurrent Two-Factor Identity Verification. According to Dr. D.J. Lee, it means that “you show your face and make the facial motion just once, you don’t have to do it twice. With the facial motion, if people want to use your photo they cannot fool the system since the photo is not moving.”
The technology first uses facial recognition and then a secret phrase is mouthed, a movement with one’s lips is made, or a facial motion is made to satisfy the second step of authentication. Even if a video is used, the chances of that video matching the secret facial motion are low.
This video could be used on a computer, cell phone, or any piece of technology with a camera on it. Dr Lee thinks there could be numerous other uses, such as to start the engine, smiling at a camera to gain access to a hotel room, using it to gain access at an ATM, and even using facial motion in disabled people to control a computer.. " We don’t necessarily limit this to unlocking a phone or mobile device. This can be used for many different applications.” he said. The next step is a demonstration of the technology with the hopes of attracting some interest of people looking to help develop the algorithm further.
NCSC: LearnG2: I-HLS: HeraldExtra:
You Might Also Read:
Google Creates Video Tools To Fight Deepfakes: