A novel video region tampering detection method based on deep neural network

Key Points

• Effective video tampering detection was achieved using deep neural network algorithms, enhancing accuracy significantly.
• Identification accuracy reached 92% for various tampered video segments, showing reliability under different conditions.
• Analysis of video data employed a novel detection algorithm featuring advanced feature extraction techniques.
• These findings support the potential for improved security measures in surveillance systems, highlighting the need for further validation.