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Blockchain-Based Reversible Data Hiding for Securing Medical Images
Author(s) -
Ji-Hwei Horng,
ChingChun Chang,
Guanlong Li,
WaiKong Lee,
Seong Oun Hwang
Publication year - 2021
Publication title -
journal of healthcare engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.509
H-Index - 29
eISSN - 2040-2309
pISSN - 2040-2295
DOI - 10.1155/2021/9943402
Subject(s) - traceability , computer science , encryption , information hiding , histogram , computer security , blockchain , embedding , hash function , block (permutation group theory) , medical diagnosis , private information retrieval , cryptography , image (mathematics) , data mining , artificial intelligence , medicine , mathematics , geometry , software engineering , pathology
Medical images carry a lot of important information for making a medical diagnosis. Since the medical images need to be communicated frequently to allow timely and accurate diagnosis, it has become a target for malicious attacks. Hence, medical images are protected through encryption algorithms. Recently, reversible data hiding on the encrypted images (RDHEI) schemes are employed to embed private information into the medical images. This allows effective and secure communication, wherein the privately embedded information (e.g., medical records and personal information) is very useful to the medical diagnosis. However, existing RDHEI schemes still suffer from low embedding capacity, which limits their applicability. Besides, such solution still lacks a good mechanism to ensure its integrity and traceability. To resolve these issues, a novel approach based on image block-wise encryption and histogram shifting is proposed to provide more embedding capacity in the encrypted images. The embedding rate is over 0.8 bpp for typical medical images. On top of that, a blockchain-based system for RDHEI is proposed to resolve the traceability. The private information is stored on the blockchain together with the hash value of the original medical image. This allows traceability of all the medical images communicated over the proposed blockchain network.

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