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Cloud Migration for Critical Enterprise Workloads: Quantifiable Risk Mitigation Frameworks
Subject area: Science,Engineering and Technology · Area of research: Cloud Migration
Abstract
Cloud computing for business-critical enterprise workloads poses considerable security, compliance, and operations risks. Organizations must overcome these risks to use cloud-based systems securely and successfully. This research provides a structured risk mitigation framework that aims to quantify, assess, and counteract threats in multi-clouds. This research offers an end-to-end approach to secure cloud adoption by discovering crucial risk factors, analyzing countermeasure solutions, and evaluating performance impacts. The framework integrates artificial intelligence (AI)-based risk modeling, predictive analytics, and compliance automation to support better decision-making. AI-based risk assessment facilitates proactive vulnerability detection, whereas predictive analytics identifies likely failures in advance. Moreover, compliance automation guarantees round-the-clock conformity to regulatory norms, minimizing the intricacies involved in manual security management. Firms can use this model in various cloud environments to increase resiliency, automate security features, and augment compliance efforts. The research also evaluates the effectiveness of different risk avoidance techniques within real-world cloud implementations, with empirical evidence for best practices. Based on the study, dynamic based on the study, dynamic risk evaluation and automated response strategies are essential tools in securing business cloud infrastructures. This research contributes to the knowledge base by providing an AI-based, scalable approach to cloud risk management. The proposed approach allows organizations to move to the cloud confidently, with security, regulatory compliance, and business efficiency in a dynamic digital world.
Keywords
Cloud Migration, Enterprise Workloads, Risk Mitigation, AI-Driven Risk Modeling, Compliance, Multi-Cloud Security
References
[1] Hubbard, D., and Sutton, M. "Top Threats to Cloud Computing: The Egregious Eleven." Cloud Security Alliance, 2020.IJRCAIT
[2] Ross, R., and Johnson, L.A. "Risk Management Framework (RMF)." National Institute of Standards and Technology, 2022.IJRCAIT
[3] Ross, R., and McEvilley, M. "Guide for Conducting Risk Assessments." NIST SP 800-30 Rev. 1, National Institute of Standards and Technology, September 2012.IJRCAIT
[4] Dekker, M., and Liveri, D. "Cloud Computing Risk Assessment." European Union Agency for Network and Information Security (ENISA), 2021.IJRCAIT+1WSJ+1
[5] Mogull, R., and Arlen, J. "Cloud Controls Matrix v4.0." Cloud Security Alliance, 2021. IJRCAIT+1WSJ+1
[6] Weber, J., and Anderson, B. "CIS Benchmarks: Cloud Security Implementation Guidelines." Center for Internet Security, 2023.IJRCAIT
[7] Barr, J., and Carter, B. "AWS Well-Architected Framework - Security Pillar." Amazon Web Services, 2023.IJRCAIT
[8] Marshall, S., and Wilson, P. "Microsoft Cloud Adoption Framework for Azure." Microsoft Corporation, 2023.IJRCAIT
[9] National Institute of Standards and Technology (NIST). "Framework for Improving Critical Infrastructure Cybersecurity." NIST Cybersecurity Framework, Version 1.1, April 2018.
[10] Cloud Security Alliance (CSA). "The Treacherous Twelve: Cloud Computing Top Threats in 2016." Cloud Security Alliance, 2016.
[11] European Union Agency for Cybersecurity (ENISA). "Cloud Computing: Benefits, Risks and Recommendations for Information Security." ENISA Report, December 2015.
[12] International Organization for Standardization (ISO). "ISO/IEC 27017:2015 - Code of Practice for Information Security Controls Based on ISO/IEC 27002 for Cloud Services." ISO Standards, 2015.
[13] International Organization for Standardization (ISO). "ISO/IEC 27018:2019 - Code of Practice for Protection of Personally Identifiable Information (PII) in Public Clouds Acting as PII Processors." ISO Standards, 2019.
[14] Federal Financial Institutions Examination Council (FFIEC). "Outsourcing Technology Services." FFIEC IT Examination Handbook, June 2015.
[15] Information Systems Audit and Control Association (ISACA). "Cloud Computing: Business Benefits with Security, Governance and Assurance Perspectives." ISACA White Paper, 2018.
How to cite this paper
@article{1702702,
author = {Adedamola Abiodun Solanke, Ph.D.},
title = {Cloud Migration for Critical Enterprise Workloads: Quantifiable Risk Mitigation Frameworks},
journal = {Iconic Research And Engineering Journals},
year = {2021},
volume = {4},
number = {11},
pages = {295-309},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1702702.pdf},
abstract = {Cloud computing for business-critical enterprise workloads poses considerable security, compliance, and operations risks. Organizations must overcome these risks to use cloud-based systems securely and successfully. This research provides a structured risk mitigation framework that aims to quantify, assess, and counteract threats in multi-clouds. This research offers an end-to-end approach to secure cloud adoption by discovering crucial risk factors, analyzing countermeasure solutions, and evaluating performance impacts. The framework integrates artificial intelligence (AI)-based risk modeling, predictive analytics, and compliance automation to support better decision-making. AI-based risk assessment facilitates proactive vulnerability detection, whereas predictive analytics identifies likely failures in advance. Moreover, compliance automation guarantees round-the-clock conformity to regulatory norms, minimizing the intricacies involved in manual security management. Firms can use this model in various cloud environments to increase resiliency, automate security features, and augment compliance efforts. The research also evaluates the effectiveness of different risk avoidance techniques within real-world cloud implementations, with empirical evidence for best practices. Based on the study, dynamic based on the study, dynamic risk evaluation and automated response strategies are essential tools in securing business cloud infrastructures. This research contributes to the knowledge base by providing an AI-based, scalable approach to cloud risk management. The proposed approach allows organizations to move to the cloud confidently, with security, regulatory compliance, and business efficiency in a dynamic digital world.},
keywords = {Cloud Migration, Enterprise Workloads, Risk Mitigation, AI-Driven Risk Modeling, Compliance, Multi-Cloud Security},
month = {May},
}