Face Recognition with Liveness Detection Login on Flask Web Application

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.

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Publication Details

Journal
International Research Journal on Advanced Engineering Hub (IRJAEH)
Published
2025-04-16
DOI
https://doi.org/10.47392/irjaeh.2025.0188
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Face Recognition with Liveness Detection Login on Flask Web Application

T Munirathinam., R. Prabakaran, S Jeevanantham, Петросян С.М.
International Research Journal on Advanced Engineering Hub (IRJAEH)
Face recognition and analysis
article

Face Recognition with Liveness Detection Login on Flask Web Application

T Munirathinam., R. Prabakaran, S Jeevanantham, Петросян С.М.
article en

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.

International Research Journal on Advanced Engineering Hub (IRJAEH)Vol. 3(04)
KPR Institute of Engineering and Technology (IN)
Openalex Percentile: Top 94%
Face recognition and analysis
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