Paper Contents
Abstract
Deepfakes are fake videos or audio created using artificial intelligence that can make people appear to say or do things they never did. This paper proposes a deepfake detection system that uses three types of data image, video, and audio to detect fake content. The system uses deep learning models to analyze visual, motion, and sound features. By combining these different sources of information, the detection becomes more accurate and reliable. The goal of this research is to help prevent the misuse of deepfake technology in harmful ways.
Copyright
Copyright © 2025 Shikha . This is an open access article distributed under the Creative Commons Attribution License.
Paper ID:
IJPREMS50700013057
ISSN:
2321-9653
Publisher:
ijprems