Deep fake Face Detection Using Deep Learning

Abstract

Advancements in artificial intelligence (AI) have significantly enhanced the ability to generate realistic deepfake videos, raising concerns about their potential misuse in domains such as political misinformation and cybercrime. To address this issue, our research presents a deep learning-based approach utilizing LBPNET, which integrates Local Binary Patterns (LBP) with Convolutional Neural Networks (CNNs). The proposed methodology involves extracting LBP features from images, training a CNN using these features, and developing a model capable of differentiating between real and fake images. The model is rigorously tested to evaluate its effectiveness in deepfake detection