DSAS 2026: Dependable and Secure Autonomous Systems

Website: https://dsas2026.github.io/

DSAS2026 is a full-day workshop at DSN 2026 focusing on the dependability and security of autonomous systems spanning space systems and drone/UAV technologies. While operating in different environments, these systems share fundamental challenges related to fault tolerance, resilience, safety, security, and assurance, especially as autonomy increasingly relies on AI and machine learning.

The workshop will put together a program in the intersection of dependable systems, security, cyber-physical systems, and autonomous platforms to examine how AI/ML-enabled autonomy changes failure modes, attack surfaces, and assurance requirements. Topics include dependable and secure sensing and communications, robustness and verification of learning-enabled components, runtime monitoring, resilience against spoofing and jamming, multi-agent and swarm dependability, and recovery from anomalies and cyber-physical incidents. DSAS2026 emphasizes open, unclassified research and aims to foster cross-domain exchange between space and UAV communities.

The workshop will accept submissions of full papers (6-pages) and short/work-in-progress papers (4-pages). Topics of interest include, but are not limited to:

Dependability and Security of Space Systems:

• Fault tolerance, resilience, and survivability of space platforms
• Failure modeling and dependability analysis under space-specific constraints
• Secure and dependable ground–space and inter-satellite communications
• Jamming, spoofing, and interference resilience
• Mission assurance and lifecycle dependability (launch, operations, decommissioning)

Dependability and Security of Drone/UAV Systems

• Fault tolerance and resilient autonomy for UAVs under resource and energy constraints
• Secure navigation and sensing (e.g., spoofing/jamming resilience, sensor fusion)
• Safety assurance, failsafe behaviors, and graceful degradation (e.g., safe landing modes)
• Dependability and security of drone swarms / multi-agent coordination
• Empirical studies, datasets, and testbeds for UAV reliability and security

AI/ML in Space and Drone/UAV Systems

• Dependability and robustness of AI/ML-enabled space components
• Verification, validation, and certification of learning-based space systems
• AI-driven autonomy, planning, and control under uncertainty
• Adversarial ML threats in space environments
• Trust, explainability, and runtime monitoring for AI in space missions
• Human–AI interaction and decision-making in mission-critical space operations

Cross-Cutting Themes

• Metrics, benchmarks, and datasets for space system dependability and security
• Secure software and hardware supply chains for space technologies
• Resilience and recovery from on-orbit anomalies or cyber-physical attacks
• Case studies and lessons learned from open, unclassified space missions

DSAS Workshop Chair:

Gokhan Kul, University of Massachusetts Dartmouth, USA