Version 1
: Received: 19 July 2023 / Approved: 20 July 2023 / Online: 20 July 2023 (11:55:45 CEST)
Version 2
: Received: 19 September 2023 / Approved: 21 September 2023 / Online: 21 September 2023 (11:24:52 CEST)
How to cite:
Zhou, C.; Zhou, Y.; Liu, X. Verifiable Privacy Preservation Scheme for Outsourcing Medical Image to Cloud Through ROI Based Crypto-Watermarking. Preprints2023, 2023071435. https://doi.org/10.20944/preprints202307.1435.v1
Zhou, C.; Zhou, Y.; Liu, X. Verifiable Privacy Preservation Scheme for Outsourcing Medical Image to Cloud Through ROI Based Crypto-Watermarking. Preprints 2023, 2023071435. https://doi.org/10.20944/preprints202307.1435.v1
Zhou, C.; Zhou, Y.; Liu, X. Verifiable Privacy Preservation Scheme for Outsourcing Medical Image to Cloud Through ROI Based Crypto-Watermarking. Preprints2023, 2023071435. https://doi.org/10.20944/preprints202307.1435.v1
APA Style
Zhou, C., Zhou, Y., & Liu, X. (2023). Verifiable Privacy Preservation Scheme for Outsourcing Medical Image to Cloud Through ROI Based Crypto-Watermarking. Preprints. https://doi.org/10.20944/preprints202307.1435.v1
Chicago/Turabian Style
Zhou, C., Yi Zhou and Xiangzhi Liu. 2023 "Verifiable Privacy Preservation Scheme for Outsourcing Medical Image to Cloud Through ROI Based Crypto-Watermarking" Preprints. https://doi.org/10.20944/preprints202307.1435.v1
Abstract
Abstract: The paper proposes a novel verifiable privacy preservation scheme for outsourcing medical image to cloud through ROI based crypto-watermarking. In the proposal scheme, data owner firstly carries out substitution of S-box for the region of interest (ROI) of medical image, and then separates the image into 4 most significant bits (MSBs) plane and 4 least significant bits (LSBs) plane images. Secondly, the hash value of ROI is embedded into the two separated bit plane images using reversible watermarking algorithm. Lastly, some selected hash values are transformed into the initial parameters of chaotic maps, and the two sharing secrets, which are produced through chaos based encryption algorithm, are finally outsourced to two different cloud servers. Authorized users can obtain shares from various cloud servers and then recover the original medical image losslessly through a series of decryption operations and watermark extraction. Furthermore, the users can verify whether the original image is completely reconstructed or not, they even can locate the tampered parts inside ROI if anyone of the sharing secrets is damaged. Some experiments are analysed and compared to show the security and effectiveness of the proposed scheme.
Keywords
sharing secret; data outsourcing; reversible watermarking; chaotic map
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
