Fake Face Detection

The advent of deepfake technology has made it possible to create extremely realistic synthetic human faces. Although these advancements demonstrate the potential of artificial intelligence, they also raise important considerations about legitimacy, security, and personal privacy. The abuse of bogus faces for identity theft, fraudulent information, and fraud highlights the crucial need for effective detection systems. Convolutional Neural Networks (CNNs), which are highly efficient in picture analysis and classification, were employed to develop a Fake Face Detection System to address this issue. The model is taught to detectminute differences between real and simulated faces. Flask was used to create a simple web app that allows people to upload photographs and get quick results. Combining deep learning and user-friendliness, the system provides both a prediction and a confidence level