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

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.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-03-04
DOI
https://doi.org/10.30574/wjarr.2025.25.3.0635
Citations
5
Primary Topic
Cloud Data Security Solutions
Type
article
Field-Weighted Citation Impact
16.23
Controls
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article

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

Ikeoluwa Kolawole
5 citations
World Journal of Advanced Research and Reviews
Cloud Data Security Solutions
16.23
article

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

Ikeoluwa Kolawole
article en
5 citations

Abstract

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.

World Journal of Advanced Research and ReviewsVol. 25(3)
Openalex Percentile: Top 1%
Cloud Data Security Solutions
16.23
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Leveraging Cloud-based ai and zero trust architecture to enhance U. S. cybersecurity and counteract foreign threats — Ikeoluwa Kolawole · World Journal of Advanced Research and Reviews (2025) | TGRS Research Map | TGRS