The Assistance of Eye Blink Detection for Two- Factor Authentication

Abstract

This paper discusses the implementation of a blink detection method using 68 facial markers and the eye aspect ratio (EAR) to provide strong protection for access systems. It investigates the importance of 68 facial markers and explores how to use eye landmarks to calculate the eye aspect ratio. Access systems, which should have good security measures and be difficult to decipher, are typically safeguarded by passwords or multi-factor verification, such as passwords combined with facial recognition. However, these methods have inherent weaknesses, including the risk of shoulder surfing with passwords and the potential to be deceived by fake face images with facial recognition. To address these issues, a two-factor authentication method by using password with eye blink recognition is proposed as an effective solution for access control. By incorporating real-time eye blinking action, the system can avoid the use of fake images and prevent shoulder spoofing. To demonstrate the practical application of eye blink detection for enhanced two-factor authentication, a web application called "Eblink" is introduced. Functional tests have been conducted to validate the application's core features.