Lightweight semantic compression visual cryptography for secure medical image transmission in IoT systems

Ensuring the secure transmission of medical images is a crucial challenge, particularly in resource-constrained IoT-based healthcare environments, where maintaining data confidentiality, integrity, and authenticity is of paramount importance. Given the sensitivity of medical data, it is imperative to develop efficient and robust security mechanisms that address the computational and storage limitations of IoT devices while ensuring reliable and secure communication. In this paper, a novel framework for lightweight visual cryptography is proposed based on semantic compression for secure transmission of medical images. The proposed framework encodes grayscale medical images into multiple visual shares to achieve confidentiality, integrity, and robust reconstruction. Modular arithmetic-based lightweight encryption techniques minimize computational overheads for IoT devices. Performance evaluation is done using medical images, with high quality reconstruction of images where PSNR is more than 34 dB, and SSIM is close to 0.99. The proposed framework is secure against tampering and eavesdropping; hence, there is robust security during transmission. This framework achieves an effective balance between computational efficiency, reconstruction quality, and security, demonstrating strong potential for secure transmission of medical images within IoT-based environments.

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Publication Details

Journal
Scientific Reports
Published
2025-12-08
DOI
https://doi.org/10.1038/s41598-025-31947-6
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
0.00

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article

Lightweight semantic compression visual cryptography for secure medical image transmission in IoT systems

Abdul Rahaman Wahab Sait, Suresh Sankaranarayanan, John Blesswin, Pascal Lorenz et al.
Scientific Reports
Chaos-based Image/Signal Encryption
article

Lightweight semantic compression visual cryptography for secure medical image transmission in IoT systems

Abdul Rahaman Wahab Sait, Suresh Sankaranarayanan, John Blesswin, Pascal Lorenz, Selva Mary G, Abdul Raouf Khan
article en

Abstract

Ensuring the secure transmission of medical images is a crucial challenge, particularly in resource-constrained IoT-based healthcare environments, where maintaining data confidentiality, integrity, and authenticity is of paramount importance. Given the sensitivity of medical data, it is imperative to develop efficient and robust security mechanisms that address the computational and storage limitations of IoT devices while ensuring reliable and secure communication. In this paper, a novel framework for lightweight visual cryptography is proposed based on semantic compression for secure transmission of medical images. The proposed framework encodes grayscale medical images into multiple visual shares to achieve confidentiality, integrity, and robust reconstruction. Modular arithmetic-based lightweight encryption techniques minimize computational overheads for IoT devices. Performance evaluation is done using medical images, with high quality reconstruction of images where PSNR is more than 34 dB, and SSIM is close to 0.99. The proposed framework is secure against tampering and eavesdropping; hence, there is robust security during transmission. This framework achieves an effective balance between computational efficiency, reconstruction quality, and security, demonstrating strong potential for secure transmission of medical images within IoT-based environments.

Scientific ReportsVol. 16(1)
SRM Institute of Science and Technology (IN), Université de Haute-Alsace (FR), King Faisal University (SA)
King Faisal University
Openalex Percentile: Top 59%
Chaos-based Image/Signal Encryption
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Lightweight semantic compression visual cryptography for secure medical image transmission in IoT systems — Abdul Rahaman Wahab Sait, Suresh Sankaranarayanan, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS