Systematic analysis of video tampering and detection techniques

Video tampering detection is a crucial research area that aims to identify and mitigate the manipulation and tampering of video content. With the widespread use of videos in various applications, ensuring the integrity and truthfulness of video data has become paramount. This research provides a thorough examination of video tampering detection strategies, encompassing both active and passive approaches. The article discusses several different kinds of tampering attacks, such as spatial, temporal, and spatiotemporal tampering, and explores the techniques used to detect these tampering instances. Moreover, the article highlights the challenges and limitations of existing techniques, such as the need for specialized hardware, the vulnerability to owner tampering, and the impact of compression artifacts. The article concludes by highlighting the future directions for research in video tampering detection, including the exploration of deepfake detection and adversarial techniques. The findings of this research provide valuable insights for developing robust and effective video tampering detection systems, thereby enhancing the trustworthiness and reliability of video content in diverse domains.