Real-Time Captcha Technique Improves Biometric Authentication | College of Computing

A short write-up on one of my recent publications.

A new login authentication approach could improve the security of current biometric techniques that rely on video or images of users’ faces. Known as Real-Time Captcha, the technique uses a unique challenge that’s easy for humans — but difficult for attackers who may be using machine learning and image generation software to spoof legitimate users. The Real-Time Captcha requires users to look into their mobile phone’s built-in camera while answering a randomly-selected question that appears within a Captcha on the screens of the devices. The response must be given within a limited period of time that’s too short for artificial intelligence or machine learning programs to respond. The Captcha would supplement image- and audio-based authentication techniques that can be spoofed by attackers who may be able to find and modify images, video and audio of users — or steal them from mobile devices.

CITATION: Erkam Uzun, Simon Pak Ho Chung, Irfan Essa and Wenke Lee, “rtCaptcha: A Real-Time CAPTCHA Based Liveness Detection System,” (Network and Distributed Systems Security (NDSS) Symposium 2018).

Source: Real-Time Captcha Technique Improves Biometric Authentication | College of Computing

Tags: , , , | Categories: Computer Vision, In The News, Machine Learning | Date: February 20th, 2018 | By: Irfan Essa |

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