Evidence map›Paper›PMID 41471577›Full record

ArticleSensors (Basel, Switzerland)2025

Edge-Enabled Hybrid Encryption Framework for Secure Health Information Exchange in IoT-Based Smart Healthcare Systems.

Norjihan Abdul Ghani, Bintang Annisa Bagustari, Muneer Ahmad, Herman Tolle, Diva Kurnianingtyas

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Norjihan Abdul GhaniDepartment of Information Systems, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur 50603, Malaysia.
Bintang Annisa BagustariDepartment of Information Systems, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur 50603, Malaysia.ORCID 0000-0002-3862-2417
Muneer AhmadDepartment of Computer Science, University of Roehampton, London SW15 5PH, UK.ORCID 0000-0001-5047-1108
Herman TolleFaculty of Computer Science, Universitas Brawijaya, Jl. Veteran No. 10-11, Malang 65145, Jawa Timur, Indonesia.
Diva KurnianingtyasFaculty of Computer Science, Universitas Brawijaya, Jl. Veteran No. 10-11, Malang 65145, Jawa Timur, Indonesia.ORCID 0000-0002-0865-7790

Funding

University of Brawijaya 01703/UN10.A0101/B/TU.01.00.1/2024University of Malaya IMG005-2023
6 · The paper itself

Abstract

The integration of the Internet of Things (IoT) and edge computing is transforming healthcare by enabling real-time acquisition, processing, and exchange of sensitive patient data close to the data source. However, the distributed nature of IoT-enabled smart healthcare systems exposes them to severe security and privacy risks during health information exchange (HIE). This study proposes an edge-enabled hybrid encryption framework that combines elliptic curve cryptography (ECC), HMAC-SHA256, and the Advanced Encryption Standard (AES) to ensure data confidentiality, integrity, and efficient computation in healthcare communication networks. The proposed model minimizes latency and reduces cloud dependency by executing encryption and verification at the network edge. It provides the first systematic comparison of hybrid encryption configurations for edge-based HIE, evaluating CPU usage, memory consumption, and scalability across varying data volumes. Experimental results demonstrate that the ECC + HMAC-SHA256 + AES configuration achieves high encryption efficiency and strong resistance to attacks while maintaining lightweight processing suitable for edge devices. This approach provides a scalable and secure solution for protecting sensitive health data in next-generation IoT-enabled smart healthcare systems.

Indexed as

Computer SecurityHealth Information ExchangeInternet of ThingsAlgorithmsCloud ComputingConfidentialityDelivery of Health CareHumansedge-enabled encryptionhealth information exchangehybrid algorithmsIoT-based smart healthcare

Identifiers

PMID41471577
PMCPMC12737280

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.