Special Track

Special Track on Security, Trustworthiness, and Runtime Governance of AI-Driven Critical Systems

With the rapid integration of artificial intelligence technologies into large-scale digital infrastructures and cyber-physical environments, security and reliability challenges are evolving from isolated model vulnerabilities to system-level operational risks. As AI systems increasingly operate as autonomous decision-making components within critical infrastructures, traditional assumptions regarding system boundaries, trust models, runtime assurance, and system controllability are being fundamentally reshaped. Compared with traditional software systems, AI-driven systems exhibit autonomous decision-making, dynamic adaptation, heterogeneous collaboration, and real-time responsiveness, which impose new requirements on system security, resilience, runtime trustworthiness, and risk-aware coordination.

This special track focuses on the security and trustworthiness of AI-enabled critical systems, including intelligent transportation systems, autonomous platforms, edge-cloud infrastructures, distributed systems, and large-scale digital services. The track aims to explore emerging challenges in secure AI orchestration, resilient autonomous decision-making, trustworthy system coordination, runtime monitoring and adaptation, and AI-driven infrastructure protection.

By promoting interdisciplinary research across AI systems, cybersecurity, distributed computing, dependable systems, and intelligent infrastructures, this special track seeks to advance the development of secure, resilient, and governable intelligent systems for next-generation critical applications.