用于司法调查的视频证据鉴定——以尼日利亚为例

B. O. Akumba, A. Iorliam, S. Agber, E. O. Okube, K. D. Kwaghtyo
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引用次数: 2

摘要

在世界各地的法庭上,视频碎片证据通常是可以接受的。然而,个人操纵这些视频来诽谤或指控无辜者。其他人则沉迷于篡改视频,以虚假地逃避法律对不当行为的愤怒。冒名顶替者伪造这些视频的一种方法是通过帧间视频伪造。因此,此类视频的完整性受到威胁。这是因为这些数字伪造严重降低了视频内容作为事件确切记录的可信度。这导致人们越来越担心视频内容的可信度。因此,它继续影响着社会和法律系统、法医调查、情报服务以及安全和监控系统。随着越来越多的视频编辑软件的出现,帧间视频伪造问题越来越自发。这些视频编辑工具可以很容易地操纵视频,而不会留下明显的痕迹,这些被篡改的视频会像病毒一样传播开来。令人担忧的是,即使是这些编辑工具的初学者,也可以通过观察来改变数字视频的内容,使其与原始内容几乎无法区分。然而,本文利用相关系数的概念,产生了一种更精细、更可靠的帧间视频检测,以帮助法医调查,特别是在尼日利亚。该模型采用了阈值的思想来有效地区分伪造视频和真实视频。使用基准和本地操作的视频数据集来评估所提出的模型。在实验上,我们的方法比现有方法表现得更好。准确度、召回率、准确度和F1分数等所有评估指标的总体准确度均为100%。所提出的方法在MATLAB编程语言中实现,已被证明可以有效地检测帧间伪造。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Authentication of Video Evidence for Forensic Investigation: A Case of Nigeria
Video shreds of evidence are usually admissible in the court of law all over the world. However, individuals manipulate these videos to either defame or incriminate innocent people. Others indulge in video tampering to falsely escape the wrath of the law against misconducts. One way impostors can forge these videos is through inter-frame video forgery. Thus, the integrity of such videos is under threat. This is because these digital forgeries seriously debase the credibility of video contents as being definite records of events. This leads to an increasing concern about the trustworthiness of video contents. Hence, it continues to affect the social and legal system, forensic investigations, intelligence services, and security and surveillance systems as the case may be. The problem of inter-frame video forgery is increasingly spontaneous as more video-editing software continues to emerge. These video editing tools can easily manipulate videos without leaving obvious traces and these tampered videos become viral. Alarmingly, even the beginner users of these editing tools can alter the contents of digital videos in a manner that renders them practically indistinguishable from the original content by mere observations. This paper, however, leveraged on the concept of correlation coefficients to produce a more elaborate and reliable inter-frame video detection to aid forensic investigations, especially in Nigeria. The model employed the use of the idea of a threshold to efficiently distinguish forged videos from authentic videos. A benchmark and locally manipulated video datasets were used to evaluate the proposed model. Experimentally, our approach performed better than the existing methods. The overall accuracy for all the evaluation metrics such as accuracy, recall, precision and F1-score was 100%. The proposed method implemented in the MATLAB programming language has proven to effectively detect inter-frame forgeries.
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