International Journal of Computer Techniques Volume 12 Issue 4 | FaceLock: A Biometric-Driven Image Encryption Model
FaceLock: A Biometric-Driven Image Encryption Model
International Journal of Computer Techniques – Volume 12 Issue 4, July – August 2025
ISSN: 2394-2231 | https://ijctjournal.org
Abstract
Facial recognition systems are increasingly used in surveillance and authentication, but they raise privacy concerns due to the sensitive nature of biometric data. This paper introduces FaceLock, a CNN-based encryption model that extracts facial features and generates dynamic hash keys for image encryption. Unlike traditional methods, FaceLock ensures that encryption is tied to biometric traits, preventing unauthorized access and model tampering. The approach enhances both recognition accuracy and data confidentiality, offering a robust solution for privacy-preserving facial recognition systems.
Keywords
Automated face recognition, CNN, Hash key, Encrypted key, Unauthorized access, Identity protection
Conclusion
FaceLock addresses the growing need for privacy in facial recognition systems by encrypting images using dynamically generated hash keys derived from CNN-extracted facial features. This ensures that sensitive biometric data remains secure throughout the training and deployment process. The model offers a scalable, secure, and privacy-preserving framework for future biometric applications, reinforcing the importance of encryption in AI-driven identity systems.
References
- E. Abusham et al., “Facial image encryption for secure face recognition system,” Electronics, 2023.
- Z. Cheng et al., “High-security privacy image encryption algorithm,” Journal of Applied Mathematics, 2022.
- L. Feng et al., “Image encryption with CNN and chaos,” Electronics, 2023.
- N. Hedayati & S. Mostafavi, “Lightweight image encryption for IoT,” Wireless Personal Communications, 2020.
- N. Jain et al., “Face-Crypt Messenger,” ICCMC, 2022.
- M. Kaur & V. Kumar, “Review on image encryption techniques,” ACM Engineering, 2020.
- S. Kamal et al., “New image encryption for medical images,” IEEE Access, 2021.
- P. Tiwari et al., “Comparison of DES, AES, RSA,” ICAC3N, 2022.
- S. Numan & Deepa, “Face recognition with image encryption,” IEEE Preprint, 2020.
- S. Patel & T. V, “Pixel confusion-diffusion encryption,” ICCES, 2022.
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