K Sitara, Mehtre B M
Centre of Excellence in Cyber Security, Institute for Development and Research in Banking Technology (IDRBT), Established by Reserve Bank of India, Hyderabad, India; School of Computer and Information Sciences (SCIS), University of Hyderabad, Hyderabad, India.
Centre of Excellence in Cyber Security, Institute for Development and Research in Banking Technology (IDRBT), Established by Reserve Bank of India, Hyderabad, India.
Forensic Sci Int. 2018 Aug;289:186-206. doi: 10.1016/j.forsciint.2018.04.056. Epub 2018 May 26.
Videos are acceptable as evidence in the court of law, provided its authenticity and integrity are scientifically validated. Videos recorded by surveillance systems are susceptible to malicious alterations of visual content by perpetrators locally or remotely. Such malicious alterations of video contents (called video forgeries) are categorized into inter-frame and intra-frame forgeries. In this paper, we propose inter-frame forgery detection techniques using tamper traces from spatio-temporal and compressed domains. Pristine videos containing frames that are recorded during sudden camera zooming event, may get wrongly classified as tampered videos leading to an increase in false positives. To address this issue, we propose a method for zooming detection and it is incorporated in video tampering detection. Frame shuffling detection, which was not explored so far is also addressed in our work. Our method is capable of differentiating various inter-frame tamper events and its localization in the temporal domain. The proposed system is tested on 23,586 videos of which 2346 are pristine and rest of them are candidates of inter-frame forged videos. Experimental results show that we have successfully detected frame shuffling with encouraging accuracy rates. We have achieved improved accuracy on forgery detection in frame insertion, frame deletion and frame duplication.
在法庭上，视频可作为证据，前提是其真实性和完整性经过科学验证。监控系统录制的视频容易受到本地或远程作案者对视觉内容的恶意篡改。这种视频内容的恶意篡改（称为视频伪造）可分为帧间伪造和帧内伪造。在本文中，我们提出了利用来自时空域和压缩域的篡改痕迹进行帧间伪造检测的技术。包含在摄像机突然变焦事件期间录制的帧的原始视频，可能会被错误地分类为被篡改视频，从而导致误报增加。为了解决这个问题，我们提出了一种变焦检测方法，并将其纳入视频篡改检测中。我们的工作还解决了目前尚未探讨的帧洗牌检测问题。我们的方法能够区分各种帧间篡改事件及其在时域中的定位。所提出的系统在23586个视频上进行了测试，其中2346个是原始视频，其余的是帧间伪造视频的候选视频。实验结果表明，我们成功地以令人鼓舞的准确率检测到了帧洗牌。我们在帧插入、帧删除和帧复制的伪造检测方面提高了准确率。
