Artificial Intelligence-Driven Zero Trust Architecture for Next-Generation Cybersecurity: Challenges, Opportunities, and a Proposed Adaptive Security Framework

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Abstract

Cyber threats are becoming more complex, digital transformation is accelerating, adoption of cloud computing is gaining momentum, remote workspaces are becoming more common, and the number of IoT devices is growing have all called into question the effectiveness of the classic perimeter-based security model. Implicit trust models used in traditional cybersecurity strategies and solutions are not sufficient to protect against advanced persistent threats, insider attacks, ransomware or AI-powered cyber-attacks. ZTA is a new paradigm in cybersecurity topics for the principle of “Always verify, never believe” At the same time, ML technologies have proven to be capable of improving threat detection, behaviour analysis, and automated counterincident response. In this writing, the authors provide an overview of the most recent developments in Zero Trust and AI-enabled cybersecurity solutions, discuss the current research needs, and present an Adaptive AI-Driven Zero Trust Security Framework (AIZTSF). This best practice combines the four key elements of continuous authentication, dynamic threat risk assessment, behavioural analytics, threat intelligence and automatic response, to improve the cyber resilience of the organisation. The research will help to enrich the body of knowledge and will serve as a blueprint for tackling the increasing cyber threats in today's digital environment.