Cognitive Trust Architecture for Mitigating Agentic AI Threats: Adaptive Reasoning and Resilient Cyber Defense

Abstract

The emergence of Agentic AI autonomous systems that can make and execute decisions without human intervention has presented new and complex challenges in cybersecurity. Traditional trust models and defense mechanisms are insufficient to handle these dynamic, intelligent threats. In this paper, we propose a novel Cognitive Trust Architecture (CTA) aimed at detecting, assessing, and mitigating agentic AI-driven cyber threats. We introduce an adaptive trust reasoning framework that continuously adjusts trust levels based on behavioral indicators, intent inference, and contextual analysis. Additionally, the framework incorporates autonomous adversary modeling to predict and counter potential attack strategies. By leveraging this approach, we demonstrate the efficacy of CTA in enhancing system integrity, reducing false positives in trust assessments, and improving resilience against evolving AI-driven adversaries. This work represents a significant advancement in applying cognitive trust as a proactive defense mechanism to counter intelligent, autonomous cyber threats.