Zero-trust security architecture in the AI era: a novel framework for enterprise cyber resilience

MAHIPAL REDDY YALLA *

SENIOR ADVISOR SERVICE DELIVERY.
 
Research Article
International Journal of Science and Research Archive, 2024, 13(02), 4341-4356.
Article DOI: 10.30574/ijsra.2024.13.2.0172
Publication history: 
Received 15 January 2024; revised on 12 December 2024; accepted on 16 December 2024
 
Abstract: 
The dependency of enterprises on artificial intelligence (AI) for operational efficiency creates new and emerging problems for cybersecurity because of threats generated by AI systems. ZTSA has replaced perimeter-based security models as a necessary means to defend against modern innovative attacks. This analysis traces the development of Zero-Trust Security systems backed by artificial intelligence for defending against contemporary malware threats and discusses their implementation practices. The analysis presents Zero-Trust's core concepts including "never trust, always verify" with micro-segmentation and continuous authentication because they strengthen enterprise resilience.
Modern cyber threats become more complicated because of AI automation through adversarial AI attacks and deepfake impersonation and automated malware distribution systems that exceed standard security protocols. Enterprises secure their operations through real-time AI-powered security features which consist of behavioral analytics plus anomaly detection and automated threat response capabilities. The research analyzes the combination of policy-driven access controls along with scalability issues and multi-cloud and hybrid cloud security consequences that affect Zero-Trust implementation.
Research demonstrates that AI systems boost Zero-Trust defense mechanisms but organizations encounter obstacles from their current legacy infrastructure together with compliance complexities and emerging attack paths. Zero-Trust adoption will benefit from the adoption of security policies that adjust according to needs and through the deployment of AI-driven monitoring solutions along with enterprise threat intelligence sharing systems for sustained improvement. The research provides specifics about conducting future work in the field through AI-based adversarial defense methods and Zero-Trust IoT and 5G approaches while evaluating ethical aspects in AI-driven cybersecurity measures.
The study expands enterprise cybersecurity research through its deep Zero-Trust Security analysis of the AI age which gives strategic direction to businesses along with security professionals and government authorities. The utilization of Zero-Trust frameworks supported by AI enables businesses to protect themselves from cyber-attacks in an age where threats are dominated by AI technology.
 
Keywords: 
Zero-Trust Security; Ai-Driven Cybersecurity; Adversarial Ai; Automated Threat Detection; Micro-Segmentation; Continuous Authentication; Ai-Powered Anomaly Detection; Enterprise Cyber Resilience; Policy-Based Access Control; Cyber Threat Intelligence
 
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