Deep Fake Detection in Social Media Forensic Taxonomy, Challenges, Future Directions
Year: 2023
Type: article
Abstract: With the rapid growth of smartphone technology, it is now commonplace to upload & download videos as part of digital social networking. More incidents are being recorded on video than ever before, so the information on them is more valuable than ever. In this paper, we give a full review of how to get information from video content & find fakes. In this context, we look at different modern methods for detecting video fakes, computer vision & (ML) methods like (DL). We also discuss recurring resource, legal, also technical issues, as well as the challenging of applying Deep learning for the task, such as the theory underpinning DL, CV, restricted, datasets, real-time processing, ML, employed with IoT-based devices. This survey also lists common video forensics analysis & investigation products. In this survey we examine video content information extraction & counterfeit detection in detail, which, as far as we know, has not been done before.
Author: Aoun, Muhammad
Institution: Ghazi University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4367704564