Video Forgery Detection for Surveillance Cameras: A Review

The widespread availability of video recording through smartphones and digital devices has made video-based evidence more accessible than ever. Surveillance footage plays a crucial role in security, law enforcement, and judicial processes. However, with the rise of advanced video editing tools, tampering with digital recordings has become increasingly easy, raising concerns about their authenticity. Ensuring the integrity of surveillance videos is essential, as manipulated footage can lead to misinformation and undermine judicial decisions. This paper provides a comprehensive review of existing forensic techniques used to detect video forgery, focusing on their effectiveness in verifying the authenticity of surveillance recordings. Various methods, including compression-based analysis, frame duplication detection, and machine learning-based approaches, are explored. The findings highlight the growing necessity for more robust forensic techniques to counteract evolving forgery methods. Strengthening video forensic capabilities will ensure that surveillance recordings remain credible and admissible as legal evidence.

@article{tayfor2025_2505.03832,
  title={ Video Forgery Detection for Surveillance Cameras: A Review },
  author={ Noor B. Tayfor and Tarik A. Rashid and Shko M. Qader and Bryar A. Hassan and Mohammed H. Abdalla and Jafar Majidpour and Aram M. Ahmed and Hussein M. Ali and Aso M. Aladdin and Abdulhady A. Abdullah and Ahmed S. Shamsaldin and Haval M. Sidqi and Abdulrahman Salih and Zaher M. Yaseen and Azad A. Ameen and Janmenjoy Nayak and Mahmood Yashar Hamza },
  journal={arXiv preprint arXiv:2505.03832},
  year={ 2025 }
}