Evidence map›Paper›PMID 39995485›Full record

ArticleBlockchain in healthcare today2024

Secure and Reliable Fog-Enabled Architecture Using Blockchain With Functional Biased Elliptic Curve Cryptography Algorithm for Healthcare Services.

Charu Awasthi, Satya Prakash Awasthi, Prashant Kumar Mishra

Abstract read
In one paragraph

Article in Blockchain in healthcare today, 2024. 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

3 authors.

Charu AwasthiResearch Scholar Department of Computer Engineering Poornima University, Jaipur, India.ORCID https://orcid.org/0000-0002-5903-2459
Satya Prakash AwasthiAssociate Professor, Department of Computer Engineering, Poornima University, Jaipur, India.
Prashant Kumar MishraAssociate Professor, Department of Computer Science and Engineering, Pranveer Singh Institute of Technology, Kanpur, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fog computing (FC) is an emerging technology that extends the capability and efficiency of cloud computing networks by acting as a bridge among the cloud and the device. Fog devices can process an enormous volume of information locally, are transportable, and can be deployed on a variety of systems. Because of its real-time processing and event reactions, it is ideal for healthcare. With such a wide range of characteristics, new security and privacy concerns arise. Due to the safe transmission, arrival, and access, as well as the availability of medical devices, security creates new issues in the area of healthcare. As an outcome, FC necessitates a unique approach to security and privacy metrics, as opposed to standard cloud computing methods. Hence, this article suggests an effective blockchain depending on secure healthcare services in FC. Here, the fog nodes gather the information from the medical sensor device and the data are validated using smart contracts in the blockchain network. We propose a functional biased elliptic curve cryptography algorithm to encrypt the data. The optimization is performed using the galactic bee colony optimization algorithm to enhance the procedure of encryption. The performance of the suggested methodology is assessed and contrasted with the traditional techniques. It is proved that the combination of FC with blockchain has increased the security of data transmission in healthcare services.

Indexed as

blockchainFB-ECCfog computingfunctional biased elliptic curve cryptography algorithmgalactic bee colony optimization algorithmGBCOAhealthcare services

Identifiers

PMID39995485
PMCPMC11848839

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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.