Lightweight signcryption scheme for Securing wearable sensor observed health data sharing in internet of medical things paradigm

The Internet of Medical Things (IoMT) plays a crucial role in enabling precision diagnosis and optimal recommendations for patients monitored remotely. However, conventional encryption-signature mechanisms introduce significant computational and communication overhead, making them unsuitable for resource-constrained IoMT devices that require secure and real-time transmission of health vitals. To address this gap, this article proposes a lightweight signcryption scheme tailored explicitly for IoMT data security. The novelty of the scheme lies in employing a triple-truncated DES-based signcryption with non-linear shared integrity verification, which simultaneously ensures confidentiality, authenticity, and resistance against replay and forgery attacks while reducing complexity. The operation increasingly adheres to critical preparation, signing, and distribution protocols even for fine-grained time periods, with truncation reaching succinct key pairs with low overhead. A lightweight CNN-based verification module is used to authenticate the sequence and handle truncation without introducing extra complexity, as required for IoMT efficiency. Experimental results demonstrate that the proposed approach improves detection accuracy by 14.12%, reduces service failures by 13.67%, and achieves computational time savings compared to baseline schemes. In all, the scheme provides an IoMT-optimized, low-complexity, and secure solution for protecting sensitive medical information against attacks in adversarial environments.

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Publication Details

Journal
Scientific Reports
Published
2025-11-20
DOI
https://doi.org/10.1038/s41598-025-24687-0
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00

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article

Lightweight signcryption scheme for Securing wearable sensor observed health data sharing in internet of medical things paradigm

Mustafa Abdullah, Rashid A. Saeed, Umi Asma’ Mokhtar, Taher M. Ghazal et al.
Scientific Reports
Cryptography and Data Security
article

Lightweight signcryption scheme for Securing wearable sensor observed health data sharing in internet of medical things paradigm

Mustafa Abdullah, Rashid A. Saeed, Umi Asma’ Mokhtar, Taher M. Ghazal, Sallam O. F. Khairy, Nada Ahmed, Shayla Islam, Mohammad Kamrul Hasan
article en

Abstract

The Internet of Medical Things (IoMT) plays a crucial role in enabling precision diagnosis and optimal recommendations for patients monitored remotely. However, conventional encryption-signature mechanisms introduce significant computational and communication overhead, making them unsuitable for resource-constrained IoMT devices that require secure and real-time transmission of health vitals. To address this gap, this article proposes a lightweight signcryption scheme tailored explicitly for IoMT data security. The novelty of the scheme lies in employing a triple-truncated DES-based signcryption with non-linear shared integrity verification, which simultaneously ensures confidentiality, authenticity, and resistance against replay and forgery attacks while reducing complexity. The operation increasingly adheres to critical preparation, signing, and distribution protocols even for fine-grained time periods, with truncation reaching succinct key pairs with low overhead. A lightweight CNN-based verification module is used to authenticate the sequence and handle truncation without introducing extra complexity, as required for IoMT efficiency. Experimental results demonstrate that the proposed approach improves detection accuracy by 14.12%, reduces service failures by 13.67%, and achieves computational time savings compared to baseline schemes. In all, the scheme provides an IoMT-optimized, low-complexity, and secure solution for protecting sensitive medical information against attacks in adversarial environments.

Scientific ReportsVol. 15(1)
Al-Ahliyya Amman University (JO), Princess Nourah bint Abdulrahman University (SA), University of Nizwa (OM), University of Lusaka (ZM), Sohar University (OM), UCSI University (MY), National University of Malaysia (MY)
Princess Nourah Bint Abdulrahman University, Universiti Kebangsaan Malaysia
Openalex Percentile: Top 81%
Cryptography and Data Security
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