Session Description

Digital twins are rapidly becoming a core enabling technology for critical infrastructure systems, supporting real-time monitoring, prediction, optimization, and operational decision-making across domains such as energy, transportation, smart cities, industrial automation, water systems, and healthcare infrastructure. At the same time, the increasing integration of digital twins with sensing platforms, communication networks, AI models, simulation environments, and control workflows creates new challenges related to cybersecurity, trust, resilience, data integrity, and model reliability.

This special session provides an international forum for researchers and practitioners working on secure, resilient, and trustworthy digital twin technologies for high-stakes environments. The session aims to bring together contributions from cybersecurity, artificial intelligence, cyber-physical systems, industrial informatics, and critical infrastructure engineering in order to explore new methods, architectures, and applications for dependable digital twin deployment.

Particular attention will be given to secure digital twin architectures, trustworthy and explainable AI, anomaly and attack detection, threat modeling, model assurance, privacy-preserving intelligence, resilient monitoring and control, and digital twin applications in critical infrastructure contexts. The session welcomes theoretical advances, methodological contributions, experimental studies, and real-world case studies.

Topics of Interest

Topics of interest include, but are not limited to:

• Secure digital twins for critical infrastructure
• Trustworthy AI for infrastructure monitoring and operation
• Cybersecurity of digital twins in energy, transport, and industrial systems
• Threat modeling and risk assessment for digital twin ecosystems
• Security of model-driven and simulation-based infrastructure systems
• Attack detection and response in digital twin environments
• Data integrity, telemetry protection, and trusted synchronization
• Robustness and resilience of AI-enabled infrastructure twins
• Secure digital twins for OT, ICS, and industrial automation
• Privacy-preserving and federated intelligence for infrastructure twins
• Edge–fog–cloud architectures for critical digital twin systems
• Explainability, assurance, and verification of twin-based decisions
• Fault diagnosis and anomaly detection in operational twins
• Secure control and resilient optimization in cyber-physical infrastructure
• Digital twin resilience under adversarial or uncertain conditions
• Smart grid, district heating, mobility, water, and urban infrastructure twins
• Standards, governance, and trust frameworks for infrastructure digital twins
• Human-centered and trustworthy decision support in critical systems