What is it about?

In today's technology age, videos are omnipresent. Everyone wants to keep their treasured memories safe. But untrustworthy persons have been known to modify these videos for the aim of committing a crime or for other reasons. As a result, videos are a problematic medium for preserving memories. Consequently, a technique for detecting video interframe forgeries has been developed. It has been observed that there is a lack of dataset availability for researchers in this discipline to validate their approach. Therefore, the study also includes a new VLFD dataset of 400 videos. The collection includes indoor, outdoor, and nature videos from Himachal Pradesh, India's most beautiful state.

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Why is it important?

Our technique restores video's trustworthiness, allowing everyone to capture their precious moments. Furthermore, the VLFD dataset enables future researchers to readily validate their approaches on higher-resolution videos.


The co-authors have a lot of expertise and I've worked with them for a long time, so writing this article was a great experience. Another result of this research was the preservation of video's credibility and a larger engagement in the creation of video dataset libraries for further study.

Himani Sharma
Punjabi University

Read the Original

This page is a summary of: Video interframe forgery detection: Classification, technique & new dataset, Journal of Computer Security, August 2021, IOS Press, DOI: 10.3233/jcs-200105.
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