The field of autonomous systems is witnessing significant advancements in real-time security and resilience. Researchers are focusing on developing innovative solutions to address the critical challenges of authentication, anomaly detection, and fault tolerance in autonomous vehicle networks and cyber-physical systems. A notable direction is the integration of artificial intelligence, blockchain, and edge computing to enhance the security, scalability, and efficiency of these systems. Noteworthy papers include SALT-V, which presents a novel hybrid authentication framework for 5G V2X broadcasting, achieving 0.035 ms average computation time and 1 ms end-to-end latency. Another significant contribution is the Hierarchical Federated Graph Attention Networks framework, which enables scalable and resilient UAV collision avoidance with a collision rate of < 2.0% and Byzantine fault tolerance of f < n/3.
Advancements in Real-Time Security and Resilience for Autonomous Systems
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SALT-V: Lightweight Authentication for 5G V2X Broadcasting
Hierarchical Federated Graph Attention Networks for Scalable and Resilient UAV Collision Avoidance
Scalable Hierarchical AI-Blockchain Framework for Real-Time Anomaly Detection in Large-Scale Autonomous Vehicle Networks
Resolving Availability and Run-time Integrity Conflicts in Real-Time Embedded Systems
A graph-informed regret metric for optimal distributed control
GeoShield: Byzantine Fault Detection and Recovery for Geo-Distributed Real-Time Cyber-Physical Systems
Towards a Formal Verification of Secure Vehicle Software Updates
Improving Resiliency of Vital Services in Flood-Affected Regions of Bangladesh Using Next-Generation Opportunistic DTN Edge Ad Hoc Networks
Cyber-Resilient Data-Driven Event-Triggered Secure Control for Autonomous Vehicles Under False Data Injection Attacks
A Quantum-Secure and Blockchain-Integrated E-Voting Framework with Identity Validation
A Comprehensive Study on Cyber Attack Vectors in EV Traction Power Electronics