Published Paper Details:

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. In this method, firstly image key points are extracted and multi-dimensional feature vector named as SIFT descriptor is generated for each key point. Then, these key points are matched using distance among their descriptors. Although this method is good at detection of copy move attacks. We can provide results about total percentage of forged and identify which frame to be forged. And design the application as window based application with image processing techniques.