VeriFace: Deepfake Detector Using Deep Learning

In an era marked by the rapid proliferation and alteration of manipulated multimedia content, deepfake technology poses a significant threat to the authenticity of digital media. This media, which includes images and videos, necessitates rigorous evaluation for deepfake detection. To address this challenge, we propose a system called VeriFace, designed to accurately differentiate between authentic and fake digital content. VeriFace leverages advanced technologies such as face recognition, face masking, and eye blinking detection to provide a robust and scalable solution for real-time deepfake identification. The system is engineered with a user-friendly interface, ensuring accessibility and ease of use. Through its innovative approach, VeriFace aims to enhance the security and authenticity of digital content, offering a crucial tool for safeguarding information in both digital and real-world contexts.