The Deepfake Detection System is an AI-driven platform developed to identify manipulated digital media, focusing on videos and images. It integrates multiple deep learning models to analyze visual artifacts and motion inconsistencies. The system is deployed through a Flask-based web application, providing users with authenticity scores, visual explanations, and secure access features. Key Points : - Detects fake videos and images using deep learning - Combines temporal and frame-level analysis for video deepfake detection - Uses ResNeXt50 + LSTM for motion inconsistency analysis in videos - Applies Xception network for frame-level artifact detection - Uses EfficientNet-B0 for image authenticity classification - Built with Flask backend and HTML/CSS/JavaScript frontend - Powered by PyTorch and TensorFlow/Keras frameworks - Provides fake probability scores and heatmaps for explainability - Includes a secure user authentication system Accuracy : ~96%