Robust AI-Enabled Security Architectures for Protecting Enterprise Workloads in Multi-Cloud Environments

Anthony Defede; Anthony Defede

doi:10.15662/IJAESIT.2024.0706005

Articles

Robust AI-Enabled Security Architectures for Protecting Enterprise Workloads in Multi-Cloud Environments

Anthony Defede

Application Engineer, Armistead Mechanical, Inc., New Jersey, United States

Abstract

The rapid adoption of multi-cloud environments has enabled enterprises to leverage diverse cloud services for enhanced flexibility, scalability, and performance. However, this distributed architecture introduces significant security challenges, including increased attack surfaces, inconsistent security policies, and complex data governance requirements. This study explores robust Artificial Intelligence (AI)-enabled security architectures designed to protect enterprise workloads across multi-cloud platforms. AI-driven techniques such as anomaly detection, behavioral analytics, automated threat intelligence, and adaptive access control are examined for their effectiveness in mitigating sophisticated cyber threats. The research highlights how machine learning algorithms can provide real-time threat detection, predictive risk assessment, and automated incident response, thereby enhancing system resilience. Additionally, AI contributes to unified security management by integrating data from multiple cloud providers and enabling centralized visibility. Despite these advantages, challenges such as interoperability, data privacy, and model transparency remain critical concerns. This study proposes a layered security architecture that combines AI capabilities with zero-trust principles and cloud-native security tools. Ultimately, AI-enabled security architectures offer a scalable and proactive approach to safeguarding enterprise workloads in increasingly complex multi-cloud ecosystems

Article Information

Journal	International Journal of Advanced Engineering Science and Information Technology (IJAESIT)
Volume (Issue)	Vol. 7 No. 6 (2024): International Journal of Advanced Engineering Science and Information Technology (IJAESIT)
DOI	https://doi.org/10.15662/IJAESIT.2024.0706005
Pages	15295-15304
Published	November 11, 2024
Copyright	Creative Commons Attribution 4.0 International License
Open Access	This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite	Anthony Defede (2024). Robust AI-Enabled Security Architectures for Protecting Enterprise Workloads in Multi-Cloud Environments. International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , Vol. 7 No. 6 (2024): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , pp. 15295-15304. https://doi.org/10.15662/IJAESIT.2024.0706005

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