Deep Fake Video Detection

Harsh Vardhan; Naman Varshney; Manoj Kiran R; Pradeep R; Dr. Latha N.R

doi:10.47392/IRJAEH.2024.0117

Authors

Harsh Vardhan UG - Computer Science and Engineering, BMS College of Engineering, Bangalore, India. Author
Naman Varshney UG - Computer Science and Engineering, BMS College of Engineering, Bangalore, India. Author
Manoj Kiran R UG - Computer Science and Engineering, BMS College of Engineering, Bangalore, India. Author
Pradeep R UG - Computer Science and Engineering, BMS College of Engineering, Bangalore, India. Author
Dr. Latha N.R Associate Professor, Computer Science and Engineering, BMS College of Engineering, Bangalore, India. Author

DOI:

https://doi.org/10.47392/IRJAEH.2024.0117

Keywords:

Long short-term memory (LSTM), ResNet, fake face image forensics, Deep Fake, Convolutional neural networks

Abstract

Deep fake technology, driven by advancements in artificial intelligence, has garnered significant attention in recent years. This paper synthesizes findings from research papers on deep fake technology, focusing on its misuse and the need for further development. The abstracts of selected papers are analyzed to identify trends, methodologies, and challenges in the field. Common themes include the generation, detection, and mitigation of deep fakes, as well as their societal and ethical implications. Through interdisciplinary collaboration, researchers strive to address the risks associated with deep fake misuse while leveraging its potential for positive applications.