A CNN-Based Multimodal Biometric Framework with Continuous Trust Scoring for Secure Web Authentication

DOI

10.2991/978-94-6239-616-6_22How to use a DOI?

Keywords

Multimodal biometrics; CNN; face recognition; voice authentication; liveness detection; continuous trust scoring; Zero Trust Access Control; web authentication; anti-spoofing

Abstract

Traditional web authentication systems face significant challenges from sophisticated spoofing attacks and lack of continuous verification mechanisms. This paper presents a novel CNN-based multimodal biometric framework that integrates face recognition, voice authentication, and liveness detection with continuous trust scoring for secure web authentication aligned with Zero Trust Access Control (ZTAC) principles. The proposed system employs deep Convolutional Neural Networks (CNNs) for facial feature extraction and anti-spoofing detection, Mel-Frequency Cepstral Coefficients (MFCC) for voice authentication, and real-time liveness detection using temporal analysis. A continuous trust scoring mechanism dynamically evaluates user authenticity throughout sessions, enabling adaptive access control. The framework addresses critical limitations of existing single-modality systems by providing robust defense against presentation attacks including photo spoofing, video replay attacks, and voice synthesis. Experimental validation demonstrates superior performance in detecting spoofing attempts while maintaining usability for legitimate users. The system’s web-deployable architecture with low-latency APIs makes it suitable for modern distributed environments requiring stringent security measures.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Vijaya Prabhu
AU  - Divakar
AU  - E. Gokulnath
AU  - J. C. Ashwin
PY  - 2026
DA  - 2026/03/31
TI  - A CNN-Based Multimodal Biometric Framework with Continuous Trust Scoring for Secure Web Authentication
BT  - Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)
PB  - Atlantis Press
SP  - 262
EP  - 275
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-616-6_22
DO  - 10.2991/978-94-6239-616-6_22
ID  - Prabhu2026
ER  -