Resilience and Security in Self-Adaptive Systems

Dear Colleagues,

Self-adaptive systems have become a cornerstone of modern computing-based infrastructures, enabling dynamic decision-making and runtime adaptation in response to changes in contextual internal and external events, and system objectives. Their ability to autonomously adjust configurations, control protocols, and resource allocations promises improved efficiency, responsiveness and scalability. However, this autonomy simultaneously increases system complexity and exposes new vulnerabilities that attract cyberattacks. Incorporating resilience and security features in self-adaptive systems remains a pressing research challenge. Such systems are expected to operate reliably either fully or in a controlled degraded mode, despite the presence of faults, component failures, and malicious cyberattacks. Addressing resiliency, security, robustness and fault tolerance must be addressed not only at the design stage but also continuously during operation, where adaptations themselves may also introduce unforeseen risks. Furthermore, traditional approaches to resilience and security are often inadequate in adaptive settings, as static or pre-defined strategies struggle to cope with evolving threats, dynamic attack surfaces, and adversarial behaviours targeting learning-based components. A key challenge in this area lies in the integration of resilience policies and security mechanisms within self-adaptive control loops. Resilience is concerned with graceful degradation, recovery, and adaptation in the face of disruption, whereas security focuses on preventing, detecting, and responding to malicious behaviour. Bridging these concerns in isolation is increasingly problematic in adaptive systems. Instead, there is a need for more holistic approaches that view resilience and security as intertwined and co-evolving properties. This shift calls for system architectures and frameworks that support adaptation by design, provide operation time assurance, and enable autonomous decision-making that remains trustworthy, with the explicit goal of sustaining system operation while avoiding, or at least minimising cascading failures. Several emerging directions are shaping the current research landscape in this area. AI-driven adaptation, including reinforcement learning and agentic AI approaches, has introduced powerful capabilities for autonomous optimisation, but it also brings renewed concerns around interpretability, robustness to adversarial influence, and the provision of safety guarantees. AI enabled digital twins enable continuous monitoring and modelling for predictive resilience and security assessment and analysis. Zero-trust architectures redefine trust assumptions in highly distributed adaptive systems, while autonomous threat mitigation techniques aim to detect, reason about, and counter cyber threats in real time without human in the loop. This special issue invites original research that advances architectures, methods, tools, and applications addressing these challenges. Contributions may include novel models, architectures, algorithms, verification techniques, or real-world case studies that demonstrate practical approaches to resilient and secure self‑adaptive systems. 

Topics of interest for this SI include but are not limited to, the following:

• AI/ML approaches for adaptive security and anomaly detection
• Security-aware adaptation and autonomous control mechanisms
• Digital twins for resilience assessment and proactive adaptation
• Resilient architectures for self-adaptive systems
• Resilience and security in IoT, edge, and fog computing systems
• Operating time monitoring, diagnosis, and self-healing mechanisms
• Formal methods and verification for adaptive and secure systems
• Human-in-the-loop adaptation and ethical considerations
• Case studies and real-world deployments of resilient adaptive systems.

Dr. Muhammad Aslam Jarwar
Dr. Aisha Kanwal Junejo
Dr. Jims Marchang
Guest Editors

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• self-adaptive systems
• resilience architecture
• fault tolerance
• autonomous systems
• anomaly detection
• IoT security
• adaptive control
• trustworthy AI
• agentic AI
• self-healing cyber-physical systems
• runtime adaptation