Evidence map›Paper›PMID 37050474›Full record

ReviewSensors (Basel, Switzerland)2023

Access Control Design Practice and Solutions in Cloud-Native Architecture: A Systematic Mapping Study.

Md Shahidur Rahaman, Sadia Nasrin Tisha, Eunjee Song, Tomas Cerny

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. 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

4 authors.

Md Shahidur RahamanDepartment of Computer Science, ECS, Baylor University, Waco, TX 76798, USA.
Sadia Nasrin TishaDepartment of Computer Science, ECS, Baylor University, Waco, TX 76798, USA.ORCID 0000-0003-4360-830X
Eunjee SongDepartment of Computer Science, ECS, Baylor University, Waco, TX 76798, USA.ORCID 0000-0002-8680-9411
Tomas CernyDepartment of Computer Science, ECS, Baylor University, Waco, TX 76798, USA.ORCID 0000-0002-5882-5502

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protecting the resources of a cloud-native application is essential to meet an organization's security goals. Cloud-native applications manage thousands of user requests, and an organization must employ a proper access control mechanism. However, unfortunately, developers sometimes grumble when designing and enforcing access decisions for a gigantic scalable application. It is sometimes complicated to choose the potential access control model for the system. Cloud-native software architecture has become an integral part of the industry to manage and maintain customer needs. A microservice is a combination of small independent services that might have hundreds of parts, where the developers must protect the individual services. An efficient access control model can defend the respective services and consistency. This study intends to comprehensively analyze the current access control mechanism and techniques utilized in cloud-native architecture. For this, we present a systematic mapping study that extracts current approaches, categorizes access control patterns, and provides developers guidance to meet security principles. In addition, we have gathered 234 essential articles, of which 29 have been chosen as primary studies. Our comprehensive analysis will guide practitioners to identify proper access control mechanisms applicable to ensuring security goals in cloud-native architectures.

Indexed as

access controlauthenticationauthorizationcloud-nativemicroservicesecurity

Identifiers

PMID37050474
PMCPMC10098865

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.