Explicit Image and Malicious URL Detection for Social Media Platforms: A Hybrid Approach Using Skin Tone Analysis, Object Detection, and Random Forest

Copyright & License

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.

BibTeX

@article{172831,
        author = {Tanmay Ghosh and Ved Khedkar and Preeti Joshi and Shraddha Mankar},
        title = {Explicit Image and Malicious URL Detection for Social Media Platforms: A Hybrid Approach Using Skin Tone Analysis, Object Detection, and Random Forest},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {1073-1077},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172831},
        abstract = {},
        keywords = {Model Building, YOLO, Random Forest, Explicit Image detection, Malicious URL detection.},
        month = {February},
        }

Cite This Article

Ghosh, T., & Khedkar, V., & Joshi, P., & Mankar, S. (2025). Explicit Image and Malicious URL Detection for Social Media Platforms: A Hybrid Approach Using Skin Tone Analysis, Object Detection, and Random Forest. International Journal of Innovative Research in Technology (IJIRT), 11(9), 1073–1077.

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