DeepFake Detection System Using Deep Learning Techniques

Abstract

Deepfake technology uses advanced artificial intelligence techniques to generate highly realistic but manipulated media content, creating serious concerns regarding authenticity and trust in digital platforms. Due to the rapid growth of social media, the spread of fake images and videos has increased significantly, leading to issues such as misinformation, identity theft, and cybersecurity threats. This study presents a Deepfake Detection System using machine learning techniques to distinguish genuine media from manipulated content. The system analyses visual features extracted from images and video frames and applies classification algorithms for detection. The proposed approach improves robustness and detection performance, providing reliable accuracy under various conditions and making it suitable for real-world applications.