Evidence map›Paper›PMID 35498196›Full record

ArticleComputational intelligence and neuroscience2022

Key Aggregation Cryptosystem and Double Encryption Method for Cloud-Based Intelligent Machine Learning Techniques-Based Health Monitoring Systems.

Khalid K Almuzaini, Amit Kumar Sinhal, Raju Ranjan, Vikas Goel, Rajeev Shrivastava, Awal Halifa

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Khalid K AlmuzainiNational Center for Cybersecurity Technologies (C4C), King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia.ORCID https://orcid.org/0000-0003-4458-3730
Amit Kumar SinhalDepartment of Computer Science and Engineering, Institute of Engineering and Technology, JK Lakshmipat University, Near Mahindra SEZ, Ajmer Road, Jaipur 302026, India.ORCID https://orcid.org/0000-0001-6697-6995
Raju RanjanSchool of Computing Science and Engineering, Galgotias University, Greater Noida, India.
Vikas GoelDepartment of IT, KIET Group of Institutions, Delhi-NCR, Meerut Road, Ghaziabad-201206, India.
Rajeev ShrivastavaDepartment of ECE, Princeton Institute of Engineering and Technology for Women, Hyderabad 500088, Telangana, India.
Awal HalifaKwame Nkrumah University of Science and Technology, Kumasi, Ghana.ORCID https://orcid.org/0000-0002-6069-6404

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cloud technology is a business strategy that aims to provide the necessary material to customers depending on their needs. Individuals and cloud businesses alike have embraced the cloud storage service, which has become the most widely used service. The industries outsource their data to cloud storage space to relieve themselves of the load of dealing with redundant data contents. This must be protected to prevent the theft of personal belongings, and privacy must be improved as well. Different research projects have been suggested to ensure the safe management of the information included within the data content. The security of current research projects, on the contrary, still needs improvement. As a result, this method has been suggested to address the security concerns associated with cloud computing. The primary goal of this study effort is to offer a safe environment for cloud users while also increasing the profit of cloud resource providers by managing and securely delivering data contents to the cloud users. The bulk of sectors, including business, finance, military, and healthcare industry, do not store data in cloud-based storage systems. This technique is used to attract these kinds of customers. Increasing public acceptance, medical researchers are drawn to cloud computing because it allows them to store their study material in a centralized location and distribute and access it in a more flexible manner. They were collected from numerous individuals who were being evaluated for medical care at the time. Scalable and enhanced key aggregate cryptosystem is a protected data protection method that provides highly effective security in the healthcare industry. When parties interested in a dispute disagree on the outflow of sensitive information, this technique manages the disputes and ensures the data security deployment of a cloud-based intelligent health monitoring system for the parties involved. The encrypted data structure of medical and healthcare prescriptions is recorded as they move through the hands of patients and healthcare facilities, according to the technique recommended. The double encryption approach is used in order to raise the overall degree of security. An encryption class is created by referring to the Ciphertext ID during the encryption procedure. The keyholder is a master secret key that facilitates in the recovery of the secret keys of various monsters and creatures by acting as a conduit between them. It is transferred and stored as a single aggregate for the benefit of the patient or customer in order to make decryption more convenient and efficient. A safe connection between cloud-based intelligent health monitoring systems and healthcare organizations and their patients may be established via the use of a key aggregation cryptosystem and a double encryption approach, according to the researchers. Because of this, when compared to earlier techniques, the findings reveal that the research methodology provides high levels of security in terms of confidentiality and integrity, in addition to excellent scalability.

Indexed as

Cloud ComputingResearch DesignCommerceHumansIntelligenceMachine Learning

Identifiers

PMID35498196
PMCPMC9050288

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.