IoT-Driven Resilience Monitoring: Case Study of a Cyber-Physical System

This study focuses on Digital Twin-integrated smart energy systems, which serve as an example of Next-Generation Critical Infrastructures (CI). The resilience of these systems is influenced by a variety of internal features and external interactions, all of which are subject to change following cyber-physical disturbances. This necessitates real-time resilience monitoring for CI during crises; however, a significant gap remains in resilience monitoring. To address this gap, this study leverages the role of Internet of Things (IoT) in monitoring complex systems to enhance resilience through critical indicators relevant to cyber-physical safety and security. The study empirically implements Resilience-Key Performance Indicators (R-KPIs) from the domain, including Functionality Loss, Minimum Performance, and Recovery Time Duration. The main goal is to examine real-time IoT-based resilience monitoring in a real-life context. A cyber-physical system equipped with IoT-driven Digital Twins, data-driven microservices, and a False Data Injection Attack (FDIA) scenario is simulated to assess the real-time resilience of this smart system. The results demonstrate that real-time resilience monitoring provides actionable insights into resilience performance based on the selected R-KPIs. These findings contribute to a systematic and reusable model for enhancing the resilience of IoT-enabled CI, advancing efforts to ensure service continuity and secure essential services for society.