Enhancing DeepFake Detection: Leveraging Mesonet for Video Fraud Identification

Machine learning, while a successful and helpful approach, has now sparked widespread public concern because of the availability of technology that can modify photographs and videos of individuals in ways that the average person cannot distinguish from the original. Digital video tampering also known as DeepFakes is what this is. Misuse of this technology has resulted in worldwide cyberbullying and threats. Various studies and research have been undertaken in recent years to understand how these movies have been tampered with and how to approach them to discover the modified videos. This study provides a thorough examination of such tampering technology and associated detection methods. In addition to making technology available to all users, we suggest a system for detecting video tampering that will aid in the comparison of original and current work due to its full explanation of the latest technology and methods, as well as datasets used in the relevant domain.