A Lightweight Hybrid Encryption and Merkle Tree–Based Security Framework for IoMT Data Storage

DOI

10.2991/978-94-6239-616-6_117How to use a DOI?

Keywords

Internet of Medical Things (IoMT); Hybrid Encryption; AES; ChaCha20; Merkle Tree; Data Integrity; Secure Storage; Cloud Security

Abstract

The Internet of Medical Things (IoMT) generates continuous streams of highly sensitive patient data that demand both strong confidentiality and real-time tamper detection during transmission and cloud storage. Traditional encryption algorithms such as AES and RSA provide strong security but are computationally expensive for low-power IoMT devices, while lightweight stream ciphers alone lack diffusion strength. This work proposes a lightweight two-layer IoMT security framework that integrates hybrid AES–ChaCha20 encryption for confidentiality and Merkle Tree–based hashing for hierarchical data integrity verification. The Edge Layer performs hybrid encryption to minimize exposure during transmission, while the Cloud Layer executes Merkle Tree validation to detect unauthorized modifications efficiently. Experimental evaluation using the UCI Heart Disease dataset demonstrates the practical advantages of the proposed model. Compared to AES-only and ChaCha20-only systems, the hybrid approach achieves a 65% reduction in encryption latency, 50% lower energy consumption, 62% higher throughput, and 6.5% improvement in analytical accuracy, with integrity verification completed in 17 ms. These results confirm that the proposed framework provides low-latency, tamper-resistant, and energy-efficient protection suitable for real-time IoMT environments. The model offers a scalable and secure foundation for next-generation digital healthcare systems requiring continuous monitoring, reliable analytics, and trustworthy cloud storage.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - S. Mary Helan Felista
AU  - M. Ganaga Durga
PY  - 2026
DA  - 2026/03/31
TI  - A Lightweight Hybrid Encryption and Merkle Tree–Based Security Framework for IoMT Data Storage
BT  - Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)
PB  - Atlantis Press
SP  - 1653
EP  - 1667
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-616-6_117
DO  - 10.2991/978-94-6239-616-6_117
ID  - Felista2026
ER  -