ROI-based medical image watermarking for accurate tamper detection, localisation and recovery
- PMID: 33990889
- DOI: 10.1007/s11517-021-02374-2
ROI-based medical image watermarking for accurate tamper detection, localisation and recovery
Abstract
Smart healthcare systems play a vital role in the current era of Internet of Things (IoT) and Cyber-Physical Systems (CPS); i.e. Industry 4.0. Medical data security has become the integral part of smart hospital applications to ensure data privacy and patient data security. Usually, patient medical reports and diagnostic images are transferred to the specialist physician in other hospitals for effective diagnostics. Therefore, the transmission of medical data over the internet has attained significant interest among many researchers. The three main challenges associated with the e-healthcare systems are the following: (1) ensuring authentication of medical information; (2) transmission of medical image and patient health record (PHR) should not cause data mismatch/detachment; and (3) medical image should not be modified accidentally or intentionally as they are transmitted over the insecure medium. Thus, it is highly essential to ensure the integrity of the medical image, especially the region of interest (ROI) before taking any diagnostic decisions. Watermarking is a well-known technique used to overcome these challenges. The current research work has developed a watermarking algorithm to ensure integrity and authentication of the medical data and image. In this paper, a novel watermarking algorithm is designed based on Integer Wavelet Transform (IWT), combined chaotic map, recovery bit generation and SHA-256 to address the objective as mentioned earlier. The paper's significant contribution is divided into four phases, namely, watermark generation and data embedding phase, authentication phase, tamper detection phase and localisation and lossless recovery phase. Experiments are carried out to prove that the developed IWT-based data embedding scheme offers high robustness to the data embedded in region of non-interest (RONI), detects and localises the tampered blocks inside ROI with 100% accuracy and recovers the tampered segments of ROI with zero MSE. Further, a comparison is made with the state-of-art schemes to verify the sternness of the developed system.
Keywords: Chaotic embedding; IWT; Localisation and lossless recovery; Patient health record; Tamper detection; Watermarking.
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