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Robust and Secure Medical Image Watermarking for Edge-enabled e-Healthcare

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Robust and Secure Medical Image Watermarking for Edge-enabled e-Healthcare. / Singh, Priyanka; Jyothsna Devi, K; Thakkar, Hiren Kumar et al.
In: IEEE Access, Vol. 11, 20.11.2023, p. 135831-135845.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Singh, P, Jyothsna Devi, K, Thakkar, HK, Bilal, M, Nayyar, A & Kwak, D 2023, 'Robust and Secure Medical Image Watermarking for Edge-enabled e-Healthcare', IEEE Access, vol. 11, pp. 135831-135845. https://doi.org/10.1109/access.2023.3335172

APA

Singh, P., Jyothsna Devi, K., Thakkar, H. K., Bilal, M., Nayyar, A., & Kwak, D. (2023). Robust and Secure Medical Image Watermarking for Edge-enabled e-Healthcare. IEEE Access, 11, 135831-135845. https://doi.org/10.1109/access.2023.3335172

Vancouver

Singh P, Jyothsna Devi K, Thakkar HK, Bilal M, Nayyar A, Kwak D. Robust and Secure Medical Image Watermarking for Edge-enabled e-Healthcare. IEEE Access. 2023 Nov 20;11:135831-135845. doi: 10.1109/access.2023.3335172

Author

Singh, Priyanka ; Jyothsna Devi, K ; Thakkar, Hiren Kumar et al. / Robust and Secure Medical Image Watermarking for Edge-enabled e-Healthcare. In: IEEE Access. 2023 ; Vol. 11. pp. 135831-135845.

Bibtex

@article{2e1ce7ce11034f1f9efdf9c6f9e43821,
title = "Robust and Secure Medical Image Watermarking for Edge-enabled e-Healthcare",
abstract = "Advancements in networking technologies have enabled doctors to remotely diagnose and monitor patients using the Internet of Medical Things (IoMT), telemedicine, and edge-enabled healthcare. In e-healthcare, medical reports and patient records are typically outsourced to a server, which can make them vulnerable to unauthorized access and tampering. Therefore, it is crucial to ensure the authorization, security, confidentiality, and integrity of medical data. To address these challenges, this paper proposes a novel reversible watermarking approach with a high payload and low computational cost. First, the input medical image is divided into a Border region (BR) and a Non-Border region (NBR). The NBR region is upscaled using Neighbour Mean Interpolation (NMI) to ensure reversibility. The Electronic Patient Record (EPR) is encrypted using a pseudorandom key, which is generated adaptively from the host medical image and the Enigma machine. The encrypted EPR is then embedded in the medical image using NMI. Two levels of tamper detection (global and local) are performed at the receiver's end for higher accuracy. A Global Integrity Code is generated and embedded in BR using LSB embedding technique for global tamper detection. The experimental results show that the visual quality and robustness are both high (Avg. PSNR = 41.03 dB and Avg. SSIM = 0.99, NC = 0.99, and BER = 0.0019 calculated for 100 images). The subjective and objective experimental analysis indicates that the proposed scheme is highly secure and the computational cost is also low. The average embedding and extraction time (including embedding, encryption and decryption, extraction process respectively) is 0.88 s and 0.83 s. It is resistant to various image processing attacks. A comparison with some of the most recent popular schemes confirms the scheme's effectiveness.",
keywords = "General Engineering, General Materials Science, General Computer Science, Electrical and Electronic Engineering",
author = "Priyanka Singh and {Jyothsna Devi}, K and Thakkar, {Hiren Kumar} and Muhammad Bilal and Anand Nayyar and Daehan Kwak",
year = "2023",
month = nov,
day = "20",
doi = "10.1109/access.2023.3335172",
language = "English",
volume = "11",
pages = "135831--135845",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS

TY - JOUR

T1 - Robust and Secure Medical Image Watermarking for Edge-enabled e-Healthcare

AU - Singh, Priyanka

AU - Jyothsna Devi, K

AU - Thakkar, Hiren Kumar

AU - Bilal, Muhammad

AU - Nayyar, Anand

AU - Kwak, Daehan

PY - 2023/11/20

Y1 - 2023/11/20

N2 - Advancements in networking technologies have enabled doctors to remotely diagnose and monitor patients using the Internet of Medical Things (IoMT), telemedicine, and edge-enabled healthcare. In e-healthcare, medical reports and patient records are typically outsourced to a server, which can make them vulnerable to unauthorized access and tampering. Therefore, it is crucial to ensure the authorization, security, confidentiality, and integrity of medical data. To address these challenges, this paper proposes a novel reversible watermarking approach with a high payload and low computational cost. First, the input medical image is divided into a Border region (BR) and a Non-Border region (NBR). The NBR region is upscaled using Neighbour Mean Interpolation (NMI) to ensure reversibility. The Electronic Patient Record (EPR) is encrypted using a pseudorandom key, which is generated adaptively from the host medical image and the Enigma machine. The encrypted EPR is then embedded in the medical image using NMI. Two levels of tamper detection (global and local) are performed at the receiver's end for higher accuracy. A Global Integrity Code is generated and embedded in BR using LSB embedding technique for global tamper detection. The experimental results show that the visual quality and robustness are both high (Avg. PSNR = 41.03 dB and Avg. SSIM = 0.99, NC = 0.99, and BER = 0.0019 calculated for 100 images). The subjective and objective experimental analysis indicates that the proposed scheme is highly secure and the computational cost is also low. The average embedding and extraction time (including embedding, encryption and decryption, extraction process respectively) is 0.88 s and 0.83 s. It is resistant to various image processing attacks. A comparison with some of the most recent popular schemes confirms the scheme's effectiveness.

AB - Advancements in networking technologies have enabled doctors to remotely diagnose and monitor patients using the Internet of Medical Things (IoMT), telemedicine, and edge-enabled healthcare. In e-healthcare, medical reports and patient records are typically outsourced to a server, which can make them vulnerable to unauthorized access and tampering. Therefore, it is crucial to ensure the authorization, security, confidentiality, and integrity of medical data. To address these challenges, this paper proposes a novel reversible watermarking approach with a high payload and low computational cost. First, the input medical image is divided into a Border region (BR) and a Non-Border region (NBR). The NBR region is upscaled using Neighbour Mean Interpolation (NMI) to ensure reversibility. The Electronic Patient Record (EPR) is encrypted using a pseudorandom key, which is generated adaptively from the host medical image and the Enigma machine. The encrypted EPR is then embedded in the medical image using NMI. Two levels of tamper detection (global and local) are performed at the receiver's end for higher accuracy. A Global Integrity Code is generated and embedded in BR using LSB embedding technique for global tamper detection. The experimental results show that the visual quality and robustness are both high (Avg. PSNR = 41.03 dB and Avg. SSIM = 0.99, NC = 0.99, and BER = 0.0019 calculated for 100 images). The subjective and objective experimental analysis indicates that the proposed scheme is highly secure and the computational cost is also low. The average embedding and extraction time (including embedding, encryption and decryption, extraction process respectively) is 0.88 s and 0.83 s. It is resistant to various image processing attacks. A comparison with some of the most recent popular schemes confirms the scheme's effectiveness.

KW - General Engineering

KW - General Materials Science

KW - General Computer Science

KW - Electrical and Electronic Engineering

U2 - 10.1109/access.2023.3335172

DO - 10.1109/access.2023.3335172

M3 - Journal article

VL - 11

SP - 135831

EP - 135845

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

ER -