文章基本信息

标题：Video Forensic Analysis Using Scalar Invariant Methodology
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作者：J.Arun ; K.Anitha ; S.Aswinimeenatchi 等
期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2021
卷号：3
期号：5
页码：865-869
DOI：10.35629/5252-0305698702
语种：English
出版社：IJAEM JOURNAL
摘要：Nowadays with the ongoing development of video editing techniques, it becomes increasingly easy to modify the digital videos. How to identify the authenticity of videos has become an important field in information security. Video forensics aims to look for features that can distinguish video forgeries from original videos. Thus people can identify the authenticity of a given video. A kind of distinguishing method which is based on video content and composed of copy-move detection and inter-frame tampering detection becomes a hot topic in video forensics. In the current times the level of video forgery has increased on the internet with the increase in the role of malware that has made it possible for any user to upload, download and share objects online including audio, images, and video. Specifically, Video Editor and Adobe Photoshop are some of the multimedia software and tools that are used to edit or tamper medial files. Added to this, manipulation of video sequence in a way that objects within the frame are inserted or deleted are among the common malicious video forgery operations. In this project, video forgery is detected that use video forgery detection in the form of features extraction from frames and matched with original videos. We can implement Scale Invariant Feature Transform (SIFT) are improved for detection of copy move attacks.