AI-Driven Dual Biometric Authentication Using Face and Voice Recognition for Secure Smart Homes
Smart homes require robust security systems to mitigate threats posed by unauthorized access. This paper proposes a dual biometric authentication system combining facial and voice recognition, empowered by deep learning models and enhanced with liveness detection and privacy-preserving algorithms. The proposed approach integrates a weighted fusion strategy, bone-conduction-based liveness detection, and homomorphic encryption. The framework is validated using simulated data and achieves an authentication accuracy of 98.3%, significantly outperforming unimodal systems.
Institutions
- Terna Dental College and Hospital (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-07-12
- DOI
- https://doi.org/10.5281/zenodo.15870746
- Primary Topic
- Biometric Identification and Security
- Type
- article
- Field-Weighted Citation Impact
- 0.00