Twajood: Two-Factor Authentication Based on Distance and Face Recognition for Secure and Efficient Employee Attendance Monitoring

Abstract

In this paper, we aim to solve critical issues organizations face during attendance monitoring. Conventional log-in systems fail to effectively ensure successful attendance monitoring, and challenges such as user manipulation, social distancing making biometric devices obsolete, and other issues arise. To address these challenges, we propose a two-factor authentication system based on distance and face recognition. The system incorporates advanced geo-tracking tools and technologies with web3 features and double-factor authentication using face recognition technologies and accompanying distance monitoring devices and tools. Our system provides secure, adaptive, and advanced log-ins for employees and attendance monitoring for employers. The proposed system is scalable by simply accompanying more distance-tracking devices with no additional support systems required. It is a smart, user-friendly, and effective log-in system designed to optimize resource and time allocation for any organization. Compared to other two-factor authentication systems, our system is faster, more secure, and does not require central devices. It is also more friendly and flexible, offering a viable solution for maintaining a safe environment and easing procedures for employees and managers.

Keywords: Adaptive systems, Face recognition, Authentication, Organizations, Social factors