A Proposed Continuous Facial Recognition Framework for Adaptive Environmental Detection

Zeeshan, Nida; Spada, Luigi La; Moradpoor, Naghmeh

Abstract

With the continuous evolution of the smart environment, the use of Internet services is becoming more common. The increased usage of these services has impacted the traditional network boundaries. This shift has created a need for more flexible, accurate and balanced approaches to cater to user authentication. Current research assumes that users, devices and processes involved in authentication within a network are trustworthy but lack in preventing attacks and managing security threats effectively. This research addresses this issue and proposes a continuous facial recognition framework based on environmental detection. This research provides a two-way mutual authentication between a user and the server. Unlike older systems, this scheme continuously monitors the user environment and uses continuous biometric authentication to authenticate the user based on the environment changes. The scheme is verified using SVO logic and supported with security and performance analysis.

Citation

Zeeshan, N., Spada, L. L., & Moradpoor, N. (2025, June). A Proposed Continuous Facial Recognition Framework for Adaptive Environmental Detection. Presented at IEEE DCOSS-IoT 2025, Tuscany (Lucca), Italy

• Presentation Conference Type: Conference Paper (published)
• Conference Name: IEEE DCOSS-IoT 2025
• Start Date: Jun 9, 2025
• End Date: Jun 11, 2025
• Acceptance Date: Apr 30, 2025
• Deposit Date: May 1, 2025
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Keywords: Authentication Protocols, Digital Authentication, Environment Detection, Biometric Authentication
• Public URL: http://researchrepository.napier.ac.uk/Output/4258812
• Publisher URL: https://ieeexplore.ieee.org/xpl/conhome/1800455/all-proceedings
• External URL: https://dcoss.org/