IoT-Enabled Reversible Watermarking of Medical Images Using PCA and Hash-Based Signatures for Secure Smart Healthcare

 

 

 

Pradeep Kumar Tripathi1, Manoj Varshney1, Aditi Sharma2,3,*

 

1Department of Computer Engineering & Applications Mangalayatan University, Aligarh, Uttar Pradesh, India

 

2Department of Computer Science and Engineering, Symbiosis Institute of Technology, Pune, India

 

3Symbiosis International (Deemed) University, Pune, India

 

Emails: er.pradeeptripathi@gmail.com; manoj.varshney_dcea@mangalayatan.edu.in;

 

Text Box: Abstract 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. aditi.sharma@ieee.org

 

Received: February 20, 2025 Revised: May 27, 2025 Accepted: July 07, 2025

 

Keywords: 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)