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Explainable Trust Calibration for Security-Critical Decisions in RIS-Assisted Integrated Sensing and Communication Systems under Eavesdropping and Adversarial Risks

Artificial Intelligence and Intelligent Systems Research, Volume 1, Issue 4, 2026 cover

Abstract

The integration of sensing and communication capabilities into a unified hardware and spectral platform represents a paradigm shift for future wireless networks. Reconfigurable Intelligent Surfaces have emerged as a transformative technology to mitigate the propagation challenges of these systems by establishing programmable wireless environments. However, the deployment of such integrated systems in environments fraught with eavesdropping and adversarial risks necessitates robust security frameworks. This paper proposes a comprehensive methodology for Explainable Trust Calibration for security-critical decisions within Reconfigurable Intelligent Surface-assisted Integrated Sensing and Communication frameworks. By leveraging explainable artificial intelligence techniques, the proposed model evaluates the trustworthiness of various nodes and communication links, dynamically adjusting the phase shifts of the intelligent surfaces to maximize the secrecy rate while maintaining high-fidelity sensing performance. The framework quantifies trust using multidimensional behavioral metrics and provides human-interpretable explanations for automated security interventions. Extensive theoretical analysis and simulation outcomes demonstrate that the proposed explainable trust calibration significantly enhances the resilience of the network against sophisticated adversarial jamming and passive eavesdropping. The integration of transparent decision-making protocols into the physical layer security domain ensures operational reliability and facilitates optimal resource allocation under stringent security constraints.

Keywords

Integrated Sensing and Communication, Reconfigurable Intelligent Surfaces, Trust Calibration, Explainable Artificial Intelligence

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