Smart and Secure Video Surveillance System with Quantum Cryptography

Surveillance systems have become indispensable across homes, institutions, industries, and public spaces, providing continuous monitoring and ensuring safety. However, as digital threats advance, conventional encryption techniques used in video surveillance are increasingly vulnerable to interception, tampering, and future quantum-based attacks. This paper presents a Smart and Secure Video Surveillance System that integrates deep-learning-based face detection with quantum cryptographic key distribution to safeguard sensitive video data. A YOLOv3-based DCNN model is utilized to detect human faces in each frame. Detected facial regions are then scrambled using a block-based transformation technique to prevent unauthorized recognition. To ensure uncompromised security, encryption keys are generated using a simulated BB84 Quantum Key Distribution (QKD) protocol, offering resistance against eavesdropping and guaranteeing key integrity. The encrypted video is transmitted securely to the monitoring unit, where decryption occurs only with quantum-authenticated keys. Experimental results demonstrate strong privacy protection, robust resistance to key interception, and reliable face detection performance, highlighting the system’s effectiveness in building next-generation, quantum-secure surveillance frameworks.