<p>This paper introduces a novel Trust-Based Security Framework designed to enhance security within IoT systems deployed in energy grid plants. By bridging the gap in the literature regarding bidirectional trust dynamics between humans and machines, our approach integrates dynamic authentication mechanisms and role-based training programs to effectively mitigate insider threats. Through systematic data collection and trust coefficient calculations, the framework assesses user reliability and competence of users within the system. Our methodology not only fortifies security measures but also promotes a culture of trust and organizational resilience. Emphasizing the importance of proactive monitoring of human behavior and vulnerability incidents to close security gaps and strengthen the robustness of critical infrastructure environments.</p>