Year: 2025
Type: article
Abstract: Secure user authentication has emerged as a critical issue due to the increased dependence on digital platforms. Conventional password-based systems are still susceptible to attacks including brute-force attacks, phishing, and credential leaks. This project uses Flask to develop a face recognition-based login system with liveness detection in order to overcome these difficulties. The solution integrates liveness detection to prevent spoofing attempts using photos, videos, or masks, and uses deep learning-based facial recognition to confirm user identity. The technology makes sure that only authorized users can access data by comparing stored encodings with real-time facial inputs. By separating authentic faces from fake ones, liveness detection improves security. This research demonstrates that incorporating biometric authentication into online applications is feasible. Despite the absence of WebRTC for live video streaming, the system offers a strong basis for future security improvements. It enhances web application access control techniques by providing a more convenient and safer substitute for password-based authentication.
Authors: Munirathinam T, Praveen Samuel P M, Prabakaran R, Jeevanantham S
Institution: KPR Institute of Engineering and Technology
Language: English
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409589030