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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Leveraging Cloud-based ai and zero trust architecture to enhance U. S. cybersecurity and counteract foreign threats

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  • Leveraging Cloud-based ai and zero trust architecture to enhance U. S. cybersecurity and counteract foreign threats

Ikeoluwa Kolawole *

College of Business, University of Louisville, Kentucky, USA.

Review Article

World Journal of Advanced Research and Reviews, 2025, 25(03), 006-025

Article DOI: 10.30574/wjarr.2025.25.3.0635

DOI url: https://doi.org/10.30574/wjarr.2025.25.3.0635

Received on 16 January 2025; revised on 24 February 2025; accepted on 27 February 2025

The increasing sophistication of cyber threats targeting U.S. national security, critical infrastructure, and financial systems necessitates a proactive, AI-driven cybersecurity strategy. Traditional security models relying on perimeter-based defenses are insufficient against state-sponsored attacks, ransomware, and advanced persistent threats (APTs). This paper explores the transformative potential of cloud-based artificial intelligence (AI) and Zero Trust Architecture (ZTA) in fortifying U.S. cybersecurity and mitigating foreign threats. Cloud-based AI enhances threat detection, real-time anomaly identification, and automated incident response by leveraging machine learning (ML), deep neural networks, and behavioral analytics. These models analyze vast amounts of network telemetry data, endpoint activities, and encrypted communications to detect evolving attack vectors with unprecedented accuracy. By incorporating federated learning and AI-driven deception techniques, cybersecurity frameworks can proactively predict and neutralize cyber threats before they materialize. Zero Trust Architecture (ZTA) further strengthens national security by enforcing continuous authentication, micro-segmentation, and least-privilege access controls. Unlike traditional models, ZTA operates under the assumption that no entity—internal or external—should be inherently trusted. By integrating cloud-native security solutions with identity-centric AI models, organizations can mitigate insider threats, secure critical infrastructure, and ensure compliance with federal cybersecurity directives. This paper examines real-world applications of AI and ZTA in national defense, critical infrastructure protection, and supply chain security, addressing implementation challenges, ethical concerns, and future research directions. The findings highlight how cloud-driven AI and Zero Trust policies are essential in safeguarding the U.S. against cyber warfare, foreign espionage, and next-generation cyber threats. 

Cloud-Based AI in Cybersecurity; Zero Trust Architecture (ZTA) for Threat Mitigation; Machine Learning for Cyber Threat Intelligence; National Security and Critical Infrastructure Protection; Automated Threat Detection and Incident Response; Foreign Cyber Threats and AI-Driven Defense Strategies

https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-0635.pdf

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Ikeoluwa Kolawole. Leveraging Cloud-based ai and zero trust architecture to enhance U. S. cybersecurity and counteract foreign threats. World Journal of Advanced Research and Reviews, 2025, 25(3), 006-025. Article DOI: https://doi.org/10.30574/wjarr.2025.25.3.0635

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.


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