Identifying Social Media Deepfake Videos Using Deep Learning Algorithms

Deepfake videos are becoming more and more common on social media, endangering privacy, security, and the dissemination of accurate information. The project "Identifying Social Media Deepfake Videos Using Deep Learning Algorithms" attempts to address this issue. The system analyzes video frames using sophisticated deep learning methods, including Convolutional Neural Networks (CNNs), to identify minute alterations typical of deepfakes. The model is trained and evaluated using a carefully selected dataset of genuine and deepfake videos, guaranteeing reliable and accurate performance. To protect digital spaces and preserve the legitimacy of online information in a time of growing manipulation, this project offers a useful tool for social media companies, law enforcement, and the general public to recognize and lessen the effects of deepfakes. Keywords—Identification of Deepfakes,CNN for Social Media Security,Analysis of Video Frames,Digital Trickery,Deep Learning Methodologies,Mitigation of Misinformation,Training using Datasets,Instantaneous Video Evaluation Recognizing False Media