Development of a Deep Fake Detection Web Application Using Machine Learning

Abstract

The emergence of deepfake technology has increased suspicions regarding the trustworthiness and authenticity of digital media specifically video content as ai-manipulation techniques have developed exponentially identifying deepfakes is more difficult than ever before to combat this challenge we introduce deep detect a comprehensive web-based system specifically built to identify fake videos driven by state-of-the-art deep learning algorithms deep detect performs fast analysis on uploaded video materials to detect fake facial areas and delivers users true real-time results it accommodates many video formats and is designed to process compressed and low-quality video providing a wide range of applications having a user-friendly interface and scalable architecture deep detect is a robust tool for the public media outlets and forensic professionals to fight the dissemination of deep fakes furthermore the system learns and evolves with continuous model updates adjusting to new deepfake methods our solution helps in the ongoing process of upholding digital media integrity and shielding against disinformation in today’s digital world.

Keywords: Deep Detect, Deep fake technology, Digital media, Real-time results, AI manipulation, Fake videos, Authenticity