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Blockchain-Enabled Secure Signature Scheme With Quantum Key Distribution for IoMT-Based Healthcare Systems.

PubMed
Authors: Prajapat S, Gautam D, Kumar P, Das AK, Pal S, Dong C

Year

2026

Paper ID

48451

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

199

Citations

2

Abstract

The rapid expansion of Internet of Medical Things (IoMT) networks has enabled continuous data collection from diverse medical sensors and devices, supporting real-time monitoring, diagnostics, and decision-making. However, the resource limitations of IoT nodes and the open nature of communication channels make healthcare data vulnerable to security and privacy breaches. To address these challenges, this paper presents a blockchain-assisted, privacy-preserving signature scheme leveraging Quantum Key Distribution \(mathcal {QKD}\) to ensure secure and trustworthy data sharing in Healthcare Internet of Things (H-IoT) environments. The proposed scheme integrates a quantum-designated verifier signature mechanism with a private blockchain infrastructure, where peer nodes validate and store healthcare data securely. Formal (software-based) and informal security analyses demonstrate the scheme's resistance to forgery, replay, and quantum attacks. Simulation experiments conducted in Python show that the proposed protocol achieves strong cryptographic performance, with a computational cost of 42.1ms and a communication overhead of 834 bits. Additionally, a blockchain-based prototype implementation quantifies the time required to append various numbers of blocks and process multiple healthcare transactions, confirming the scalability and practicality of the proposed solution. The results affirm that the scheme offers a reliable, efficient, and quantum-resilient framework for securing sensitive medical data across distributed IoMT healthcare systems.

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  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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  • The rapid expansion of Internet of Medical Things (IoMT) networks has enabled continuous data collection from diverse medical sensors and devices, supporting real-time...

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