Neuromorphic Digital Twin Architectures for Adaptive Cybersecurity in Smart Infrastructure

Review Article

Abstract

The rapid adoption of smart infrastructure has significantly increased the complexity and connectivity of critical systems, including smart cities, intelligent transportation, healthcare networks, industrial automation, and smart energy grids. While digital transformation improves operational efficiency and automation, it also expands the cyberattack surface, making conventional security approaches increasingly inadequate against sophisticated and evolving threats. Neuromorphic computing and Digital Twin technologies have recently emerged as promising solutions for developing adaptive, intelligent, and energy-efficient cybersecurity systems. Neuromorphic computing emulates the information-processing mechanisms of the human brain through event-driven architectures and Spiking Neural Networks (SNNs), enabling real-time anomaly detection with low power consumption. Digital Twins provide virtual representations of physical assets that continuously synchronize with real-world systems, allowing proactive monitoring, threat simulation, and predictive security management. This review examines the integration of neuromorphic computing and Digital Twin architectures for adaptive cybersecurity in smart infrastructure. The paper discusses the principles of neuromorphic intelligence, Digital Twin technology, adaptive cyber defense, enabling technologies, and future research directions. The review highlights how brain-inspired intelligence and real-time virtual modeling can improve cyber resilience, operational reliability, and sustainable security management in next-generation smart infrastructure.