2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 18 , Issue 1 , PP: 126-139, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Pradeep Kumar Tripathi 1 , Manoj Varshney 2 , Aditi Sharma 3 *
Doi: https://doi.org/10.54216/JISIoT.180109
The rise of IoT in smart healthcare systems necessitates secure and efficient methods to protect sensitive medical imaging data transmitted across interconnected devices. This research introduces a novel IoT-enabled reversible watermarking technique using Principal Component Analysis (PCA) and Hash-Based Signatures (HBS) to ensure both data integrity and diagnostic quality. The method supports secure embedding of watermarks into medical images captured and transmitted by IoT devices such as wearable scanners, remote diagnostic units, and edge sensors. By leveraging PCA for minimal distortion and reversible embedding, and HBS for robust tamper detection, the system ensures full restoration of original images post-verification. Discrete Wavelet Transform (DWT) further optimizes the compression and transformation for real-time IoT environments. The proposed approach demonstrates high imperceptibility (high PSNR), robust tamper detection (using SHA-256 and SHA-512), and full reversibility, making it ideal for real-time transmission of medical data over IoT-based healthcare networks.
Reversible Watermarking , Discrete Wavelet Transform (DWT) , Principal Component Analysis , Peak Signal-to-Noise Ratio , Normalized Correlation , Structural Similarity Index Measure , Mean Squared Error , Hash-Based Signatures Techniques (HBST) , Internet of things (IoT)
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