• AI-Powered Policy Formulation...

Treffer: AI-Powered Policy Formulation and Enforcement in Zero Trust Frameworks

Title:
AI-Powered Policy Formulation and Enforcement in Zero Trust Frameworks
Authors:
Meccy Joy, Srinivasan Venkataramanan
Publication Year:
2025
Subject Terms:
Gender, policy and administration, Artificial intelligence not elsewhere classified, System and network security, Cybersecurity and privacy not elsewhere classified, Information security management, Adversarial machine learning, Ethical use of new technology, Artificial intelligence - Data processing, Zero Trust Architecture, Cybersecurity Policy, policy enforcement, machine learning analyses, Behavioral Analytics, Identity and Access Management, access control and management, threat detection, Explainable AII, context-aware pattern analysis, data protection security, Security Automation, Privacy Compliance, Network security
Document Type:
dataset
Language:
unknown
DOI:
10.6084/m9.figshare.29094935.v1
Availability:
https://doi.org/10.6084/m9.figshare.29094935.v1
https://figshare.com/articles/dataset/_b_AI-Powered_Policy_Formulation_and_Enforcement_in_Zero_Trust_Frameworks_b_/29094935
Rights:
CC BY 4.0
Accession Number:
edsbas.80A07F79
Database:
BASE

Weitere Informationen

This article, "AI-Powered Policy Formulation and Enforcement in Zero Trust Frameworks" , authored by Srinivasan Venkataramanan, Dheeraj Kumar Pal, Kalyan Sandu, Ashok Kumar Reddy Sadhu, Leeladhar Gudala, Mohammed Ahmed, and Meccyjoy , explores the fusion of Artificial Intelligence (AI) and Zero Trust security architectures to enhance policy enforcement in modern digital ecosystems. The study addresses the limitations of traditional, static security policies and demonstrates how AI, through machine learning, natural language processing, and behavior analytics, can dynamically craft, adapt, and enforce context-aware security policies in real time. Real-world use cases, such as Google’s BeyondCorp and Microsoft Conditional Access, illustrate the practical application of AI in Zero Trust systems. The paper also discusses critical challenges, including bias in AI models, privacy concerns, explainability, and balancing usability with security. This research contributes significantly to the discourse on AI-powered cybersecurity, proposing a proactive, scalable approach to defend against evolving threats in cloud and hybrid environments. It highlights the importance of explainable AI (XAI), quantum resilience, and cross-industry collaboration in building ethical, transparent, and robust Zero Trust security frameworks for the future.