Deepfake Detection System

Author(s)	Ms. L.T Priyanka, Mr. Ch. Durga Rao, Ms. P. Kanakamahalakshmi, Ms. B. Durga Madhuri, Mr. K. Om Sarvan, Mr. K. Kushwanth Kumar
Country	India
Abstract	Deepfake technology, powered by advanced deep learning techniques like Generative Adversarial Networks (GANs), can create highly realistic fake images and videos. While useful in media and entertainment, it raises serious concerns about privacy and security. This project presents a deepfake detection system that uses a Convolutional Neural Network (CNN) with a fine-tuned XceptionNet model to classify media as real or fake. The system processes data through frame extraction, face detection, and preprocessing and is trained on datasets like FaceForensics++. It detects visual inconsistencies and artifacts, helping improve digital media security.
Keywords	Deepfake Detection, Deep Learning, CNN, XceptionNet, GAN, FaceForensics++, Video Forensics
Field	Engineering
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-05

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International Journal For Multidisciplinary Research