The rapid growth of video content on cloud platforms has significantly increased storage requirements and data redundancy due to duplicate videos. Traditional video copy detection techniques require access to raw video data, which leads to serious privacy and security concerns. To overcome this problem, the proposed system introduces a privacy-preserving video copy detection method using homomorphic encryption. This technique allows computation to be performed directly on encrypted data without the need for decryption. In this system, videos are encrypted before being uploaded to the cloud server. The encrypted videos are then processed to extract features required for comparison. Duplicate detection is performed by comparing encrypted video data with existing stored videos. If a duplicate is identified, the system avoids storing the video again and instead creates a reference link to the original video. [1].

This approach helps in reducing storage space and eliminating redundancy. The system ensures that sensitive video data is never exposed during processing. It also provides modules such as user registration, login, video upload, duplicate detection, and download. The implementation demonstrates that the system can accurately identify both unique and duplicate videos. It maintains a balance between privacy, efficiency, and functionality.