Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{190582,
        author = {Hima Mariya T and IRINE ROSE V CHAZHOOR and KARTHIKA K and SUDEEPTH SASIKUMAR and ANJANA B},
        title = {Multi-Modal Semantic Distillation For Image Forgery Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {4432-4436},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190582},
        abstract = {In today’s digital era, multimedia content such as images, videos, and audio plays a crucial role in communication, entertainment, and information sharing. However, with the rapid advancement of digital editing tools, forgery and manipulation of multimedia data have become easier, posing serious challenges to authenticity, privacy, and trust. Multimedia forgery detection is a system designed to identify and prevent the misuse or alteration of digital media. This project aims to develop a secure and efficient platform that allows the detection of forged multimedia content while maintaining user interaction and complaint management. The system includes three major roles: Admin, Cybercell, and User. The Admin manages user verification, cybercell approvals, and complaint handling. The Cybercell acts as the investigation authority, analyzing multimedia data for forgery (image, video, and audio) and taking appropriate actions such as blocking or unblocking users. The User can register, share posts, interact through comments and chats, and file complaints against suspicious activities or fake content. The system integrates multimedia forgery detection modules to analyze suspicious media and generate authenticity reports. This ensures a secure digital environment and helps law enforcement authorities handle cyber-related cases more efficiently.},
        keywords = {Image Forgery, Artificial Intelligence, Deep Learning, Social Media Security, Audio Forgery},
        month = {January},
        }