Deepfake Detection in Videos and News

Akash Panchal, Yuvraj Khade, Purab Gandhi, Tushar Rathod and Tejas Sapkal

International Journal of Scientific Research in Artificial Intelligence and Machine Learning, 2026, vol. 2, issue 3, 230-237

Abstract: The rapid advancement of Artificial Intelligence (AI) and digital media technologies has significantly increased the creation and dissemination of deepfakes, fake news, manipulated images, synthetic audio, and misleading online content. These forms of digital deception pose serious threats to public trust, information integrity, cybersecurity, and social stability. Traditional verification methods often rely on manual fact-checking and expert analysis, which can be time-consuming, resource-intensive, and ineffective against the growing volume of online misinformation. Individuals, journalists, organizations, and government agencies frequently face challenges in identifying fabricated content, verifying authenticity, and preventing the spread of false information. To address these challenges, this project presents a Deepfake and Misinformation Detection System called GuardianAI, an intelligent platform designed to detect and analyze fake news, manipulated images, deepfake videos, and AI-generated audio content. The system is developed using React.js, FastAPI, MongoDB, Scikit-Learn, PyTorch, TensorFlow, OpenCV, Librosa, and various Machine Learning and Deep Learning technologies.

Keywords: Deepfake Detection; Fake News Detection; Misinformation Analysis; Artificial Intelligence; Machine Learning; Deep Learning; Natural Language Processing; Computer Vision; Audio Deepfake Detection (search for similar items in EconPapers)
Date: 2026
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