International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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IFAKE: Intelligent Video Forgery Detection System

Author(s) Ms. AYISHA KHANUM, Ms. HITHAISHI U, Mr. SHADABUR RAHAMAN, Ms. SUSHMITHA M J, Ms. VANISHREE M
Country India
Abstract The growing proliferation of deepfake content and AI-generated media has created an immediate need for reliable systems that can verify video authenticity to prevent misinformation. iFAKE: AI-Driven Video Forgery Detection System is an advanced platform designed to overcome some of the key challenges: rapid deepfake generation, manual verification difficulties, and lack of real-time detection tools. The system integrates multiple deep learning models-EfficientNet, MesoNet, YOLO, and Vision Transformers-that analyze both spatial and temporal patterns in videos for manipulation prediction, along with confidence-based detection results. It provides intuitive, role-based access via user and admin portals, thus enabling seamless usage, monitoring, and result management. As such, it allows users to upload videos for instant AI analysis while enabling administrators to track logs, model performance, and system activity. This improves the efficiency of verification and further consolidates trust in digital communications with manipulation-region visualization, real-time processing, and secure handling of media files. It supports global needs by facilitating safer online media consumption and assists institutions in combating misinformation at scale.
Keywords deepfake detection, video forgery, EfficientNet, Vision Transformer, media authentication, real-time detection, computer vision
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-05
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.62557
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E-ISSN 2582-2160
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