ArticleHeliyon2024
A secure and privacy preserved data aggregation scheme in IoMT.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed.
- A MITRE D3FEND guided blockchain based cyber resilient framework for IPv6 based 6G enabled healthcare networks.Scientific reports · 2026Article
- Secure IoMT smartwatch-based blood glucose monitoring using multimodal activity and nutrition data with transfer learning.Scientific reports · 2026Article
- Scalable privacy-preserving data analytics for IoMT via FHE and zk-SNARK-enabled edge aggregation.Scientific reports · 2026Article
- Privacy-by-Design Framework for Large Language Model Chatbots in Urology.International neurourology journal · 2025Article
- Quantum-resilient and adaptive multi-region data aggregation for IoMT using zero-knowledge proofs and edge intelligence.Scientific reports · 2025Article
- A Secure Data Aggregation Algorithm Based on a Trust Mechanism.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Internet of Things (IoT) is a network of intelligent devices especially in healthcare-based systems. Internet of Medical Things (IoMT) uses wearable sensors to collect data and transmit to central repositories. The security and privacy of healthcare data is a challenging task. The aim of the study is to provide a secure data sharing mechanism. The existing studies provide secure data sharing schemes but still have limitations in terms of hiding the patient identify in the messages exchanged to upload the data on central repositories. This paper presents a Secure Aggregated Data Collection and Transmission (SADCT) that provides anonymity for the identities of patient's mobile device and the intermediate fog nodes. Our system involves an authenticated server for node registration and authentication by saving security credentials. The proposed scheme presents the novel data aggregation algorithm at the mobile device, and the data extraction algorithm at the fog node. The work is validated through extensive simulations in NS along with a security analysis. Results prove the supremacy of SADCT in terms of energy consumption, storage, communication, and computational costs.
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Registered trials
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.