CORE: c QUALIS: b3 Viewed: 40316 Tracked: 13 Attend: 2
Call For Papers
DASC 2025 (International Conference on Dependable, Autonomic and Secure Computing) is a CORE C / QUALIS B3 conference held in Hokkaido, Japan on 2025-10-21. The paper submission deadline is 2025-06-10. Acceptance notifications are sent on 2025-08-11.
As computer and communication systems, as well as other systems such as Cyber-Physical Systems (CPS), Internet of Things (IoT), and Autonomous Robotic Systems, become increasingly large and complex, their Dependability and Security play critical roles in supporting next-generation science, engineering, and commercial applications. It remains a challenge to design, analyze, evaluate, and improve the dependability and security of a large-scale computing environment. Trusted and autonomic computing/autonomous systems need synergistic research efforts covering many disciplines, from natural sciences to social sciences. It requires scientific and technological advances in a variety of fields, as well as new software, architectures, communication, and data platform technology that support the integration of the constituent technologies.
IEEE DASC 2025 will be held during October 21-24, 2025, in Hakodate, Japan, co-located with IEEE CyberSciTech 2025, IEEE PICom 2025, and IEEE CBDCom 2025. It aims to bring together computer scientists, industrial engineers, and researchers to discuss and exchange theoretical and implementation results, novel designs, work-in-progress, experience, case studies, and trend-setting ideas in the areas of dependability, security, trust, and/or autonomic computing, and autonomous systems.
Topics of interest include, but are not restricted to: Self-Organization and Organic Computing; Cognitive Computing and Self-Aware Computing; Energy Management in Autonomic Computing and Autonomous Systems; Dependable & Fault-tolerant Computing in Big Data, CPS, IoT, SDN, and Real-time System; Hardware and Software Reliability, Verification and Testing; Security and Privacy in Cloud/Fog/Edge Computing, Mobile and Pervasive Computing, Big Data, CPS and IoT systems; Artificial Intelligence Techniques in Network and System Security and Privacy; Autonomic and Autonomous Issues in Cloud/Fog/Edge Computing, Mobile and Pervasive Computing, Big Data, CPS and IoT systems; Software/Apps/Tools Development for Dependable and Secure Applications; IoT and Sensor Network, Big Data, Smart Grid, Aerospace, Transportation Applications.
Track 1. Dependability, Reliability, and Fault Tolerance
• Fault-tolerant hardware and software architectures
• Hardware and software reliability, verification and testing
• Reliability modeling and prediction for complex systems
• Highly Reliable Systems achieving stable performance
• Resilience engineering in Cyber-Physical Systems (CPS)
• Redundancy design for critical infrastructure
• Dependability metrics and evaluation frameworks
• Simulation, verification, testing, and validation for autonomous systems
Track 2. Security, Privacy, and Trust in Systems and Networks
• Intrusion detection, prevention, and mitigation in networked environments
• Security modeling, auditing and compliance in safety-critical systems
• Self-adaptive security architecture, techniques, and algorithms
• Security protocols for CPS, IoT, and autonomous systems (e.g., vehicles, drones, robots)
• Data protection for networked systems and storage systems
• Privacy-preserving techniques for distributed and autonomous system
• Blockchain for trustworthy and secure system design
• Cryptographic methods for secure computing, storage and communication
• Post-quantum cryptography for future-proof security
• Trust management in distributed and autonomous systems
Track 3. Autonomic Computing and Self-Adaptive Systems
• Self-adaptive software architectures for autonomic computing
• Adaptive computing, communication, and resource allocation for autonomic systems
• Self-healing mechanisms for autonomic systems
• Autonomic decision-making under uncertainty
• Embodied AI for physical system adaptation
• Self-optimization for energy-efficient autonomic systems
• Modeling and STV & V of self-adaptive behaviors
Track 4. AI, Machine Learning, and Advanced Computational Methods
• AI-driven threat prediction, anomaly detection, fault detection and diagnosis
• Large Language Models (LLMs) for system specification and verification
• Data platforms leveraging and powering AI
• Quantum computing applications in dependability analysis
• Generative AI for synthetic test case generation
• Explainable AI for trustworthy autonomic computing
• Trustworthy and safe AI-empowered systems
Track 5. Industrial Applications and Case Studies
• Dependability and security solutions in safety-critical control systems in transportation and aerospace industries
• Autonomous systems in industrial IoT deployments
• Case studies on CPS reliability in manufacturing
• Lessons learned from autonomous vehicle system deployments
• Real-world applications of trustworthy AI in various industrial sectors