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Publication Type : Conference Paper
Source : The 15th International IEEE Conference on Computing, Communication and Networking Technologies (ICCCNT) , IIT Mandi, 2024
Campus : Bengaluru
School : School of Engineering
Department : Electrical and Electronics
Year : 2024
Abstract : 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.
Cite this Research Publication : S Babitha, Vikram Sundaram, Susmitha Vekkot, "Enhancing Deep fake Detection: Leveraging Deep Models for Video Authentication", The 15th International IEEE Conference on Computing, Communication and Networking Technologies (ICCCNT) , IIT Mandi,, June 24-28, 2024