Intelligent Image Rights Protection System Using Machine Learning, Cloud Services and IoT Alerts - S. P. Yaamini; K. Sivaranjani; B. Nujithra; V. Anitha (Journal of Technology Informatics and Engineering, 2026)
The rapid growth of digital media platforms has intensified the misuse of images through unauthorized manipulation, morphing, and non-consensual redistribution, posing significant threats to individual privacy and intellectual property rights. Despite the availability of reporting and takedown mechanisms, their effectiveness remains limited due to procedural complexity, delayed response times, and concerns regarding user anonymity. This paper presents the Smart Image Rights Protection (SIRP) system, a user-centric framework designed to detect, monitor, and respond to unauthorized use of images in online environments. The proposed system utilizes perceptual hashing to generate resilient digital fingerprints for registered images, enabling accurate identification after common transformations such as resizing, cropping, and minor visual alterations. A cloud-ready similarity analysis module is designed to support scalable matching in future deployments, while the current evaluation is conducted on a controlled dataset. An IoT-enabled hardware interface provides real-time alerts to users upon detection of potential misuse. Experimental results on controlled manipulation scenarios show that SIRP achieves detection accuracy of 95.6% for resized images and 94.3% for cropped images, outperforming traditional pixel-based comparison methods. Furthermore, automated evidence logging and instant notifications substantially reduce the latency between detection and user response actions. By combining robustness under common transformations, cloud-assisted processing, and timely user engagement, SIRP offers a practical solution for protecting digital image ownership and personal privacy.