Home
Magna Scientia Advanced Research and Reviews
Peer-Reviewed • ISSN: 2582-9394 • Fast-Track Publishing • Impact Factor 8.5 • Low Publication Charges • Crossref DOI Linking

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

Research and review articles are invited for publication in September - October 2026 (Volume 18, Issue 1) Submit manuscript

Comprehensive data security and compliance framework for SMEs

Breadcrumb

  • Home
  • Comprehensive data security and compliance framework for SMEs

Zein Samira 1, *, Yodit Wondaferew Weldegeorgise 2, Olajide Soji Osundare 3, Harrison Oke Ekpobimi 4 and Regina Coelis Kandekere 5

1 Cisco Systems, Richardson, Texas, USA.
2 Deloitte Consulting LLP, Dallas, TX, USA.
3 Nigeria Inter-bank Settlement System Plc (NIBSS), Nigeria.
4 Shoprite, Cape Town, South Africa.
5 Independent Researcher, Dallas Texas, USA.
 
Review Article
Magna Scientia Advanced Research and Reviews, 2024, 12(01), 043-055
Article DOI: 10.30574/msarr.2024.12.1.0146
DOI url: https://doi.org/10.30574/msarr.2024.12.1.0146
Received on 15 August 2024; revised on 24 September 2024; accepted on 27 September 2024
Small and Medium-sized Enterprises (SMEs) are increasingly relying on cloud platforms to support critical business operations, making effective disaster recovery (DR) strategies essential for ensuring business continuity. This review proposes a robust disaster recovery framework tailored for SMEs, designed to minimize downtime and data loss in the event of a system failure, cyberattack, or natural disaster. The framework integrates advanced cloud technologies to create a cost-effective, scalable solution that aligns with the resource constraints of SMEs while providing enterprise-grade resilience. Key components of the disaster recovery framework include cloud-based data replication, automated backup solutions, and geo-redundant storage to ensure that data is continuously available and recoverable. This model employs real-time data synchronization and incremental backups to minimize Recovery Point Objectives (RPO), ensuring that critical data is not lost during an unexpected outage. Additionally, the framework leverages automated failover mechanisms to achieve low Recovery Time Objectives (RTO), allowing businesses to restore operations quickly after an interruption. Cloud orchestration tools such as AWS Elastic Disaster Recovery or Azure Site Recovery are utilized to automate disaster recovery processes, reducing manual intervention and improving the speed of recovery. The framework also incorporates regular testing of disaster recovery plans, using simulation tools to identify weaknesses and optimize response times. For SMEs, cost-effectiveness and ease of management are crucial. The framework emphasizes a pay-as-you-go model for cloud resources, allowing businesses to scale their disaster recovery solutions as they grow without incurring excessive upfront costs. By providing continuous monitoring and proactive threat detection, this disaster recovery framework ensures that SMEs can maintain uninterrupted business operations on cloud platforms, thereby enhancing resilience and mitigating the financial and operational risks associated with data loss and system downtime.
Data Security; Framework; SMEs; Review
https://msarr.magnascientiapub.com/sites/default/files/fulltext_pdf/MSARR-2024-…

Preview Article PDF

Zein Samira, Yodit Wondaferew Weldegeorgise, Olajide Soji Osundare, Harrison Oke Ekpobimi and Regina Coelis Kandekere. Comprehensive data security and compliance framework for SMEs. Magna Scientia Advanced Research and Reviews, 2024, 12(1), 043-055. Article DOI: https://doi.org/10.30574/msarr.2024.12.1.0146

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 Magna Scientia Advanced Research and Reviews - All rights reserved

Developed & Designed by VS Infosolution