Abstract Surveillance videos and footages are the primary sources of evidence for any event or crime in the court of law. However, with the rapid advent of low-cost, computationally cheap video manipulating software and tools, video manipulation has become a no-brainer task today. This introduces a major challenge in authenticating the sanctity/originality of videos before they can be produced in the court, or used in other sensitive application domains. In this paper, we propose a digital forensic technique to detect inter-frame forgeries in surveillance videos. The proposed technique utilizes compressed domain video footprints i.e, prediction footprint variation and variation of motion vectors in videos, for the purpose of video forgery detection and localization. Through this work, we identify the type of forgery that has taken place in a video. We have performed experiment over 43 authentic and 720 inter-frame forged videos. Our experimental results indicate that the proposed technique performs consistently efficiently, irrespective of the group of pictures length and degree of compression in videos.

中文翻译：

---

基于宏块变化和运动矢量分析的视频帧间伪造检测与定位

摘要 监控视频和录像是法庭上任何事件或犯罪的主要证据来源。然而，随着低成本、计算成本低廉的视频处理软件和工具的迅速出现，视频处理在今天已成为一项不费吹灰之力的任务。这给在法庭上制作或用于其他敏感应用领域之前验证视频的神圣性/原创性带来了重大挑战。在本文中，我们提出了一种数字取证技术来检测监控视频中的帧间伪造。所提出的技术利用压缩域视频足迹，即预测足迹变化和视频中运动矢量的变化，用于视频伪造检测和定位。通过这项工作，我们确定了视频中发生的伪造类型。我们已经对 43 个真实和 720 个帧间伪造视频进行了实验。我们的实验结果表明，无论视频中的图片长度和压缩程度如何，所提出的技术都能始终有效地执行。