Uncertainty-aware knowledge representation and reasoning in critical infrastructure systems

As socio-technical Cyber-Physical Systems (CPS), and Critical Infrastructure (CIs) in particular, become increasingly complex and interdependent, there is a growing need for integrated approaches that support decision-making across a wide range of domains. These domains rely on diverse, often heterogeneous data streams subject to uncertainty and involve multiple, sometimes conflicting concerns (technical, economic, environmental, and social). While recent frameworks have attempted to integrate various data sources for decision support, they frequently remain limited to operational insights and lack structured mechanisms for uncertainty-aware reasoning. This limitation hinders effective cross-domain decision-making and the comprehensive evaluation of non-technical factors. In response to these challenges, we propose a generic, hybrid reasoning framework designed to support uncertainty-aware assessment and adaptive decision-making. Our approach enables: (1) the creation of a structured knowledge representation, equipped with an explicit measure of uncertainty; (2) the formal specification of diverse system requirements and cross-domain concerns through a shared conceptual foundation; and (3) the abductive generation of behavioral hypotheses and the evaluation of their plausibility across multiple dimensions, dynamically updated as new uncertain data becomes available. Applications include, but are not limited to, operational efficiency, resource optimization, public safety, resilience and business continuity monitoring. To demonstrate the applicability of our framework, we apply it to the domain of critical infrastructure resilience, using real-world traffic data from Portugal’s Norte Litoral highway. A simulated cyber-attack targeting traffic control systems is employed to analyze cascading impacts on emergency services, urban mobility, and public behavior. The results confirm the framework’s capability to detect behavioral drift and evaluate performance across both technical and societal dimensions. Additionally, preliminary feedback on the framework’s practical relevance was obtained during a hackathon event focused on resilience assessment.