TITLE:
Authentication of Video Evidence for Forensic Investigation: A Case of Nigeria
AUTHORS:
Beatrice O. Akumba, Aamo Iorliam, Selumun Agber, Emmanuel Odeh Okube, Kenneth Dekera Kwaghtyo
KEYWORDS:
Inter-Frame, Video Forgery, Correlation Coefficients, Forensic Investigation, Threshold
JOURNAL NAME:
Journal of Information Security,
Vol.12 No.2,
April
29,
2021
ABSTRACT: 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.