As critical cyber-physical systems, urban transport systems are vulnerable to natural disasters and deliberate attacks. Ensuring their resilience is crucial for sustainable operations and includes the ability to withstand, absorb and recover efficiently from disruptions. Assessing the resilience of such systems requires a comprehensive set of performance indicators covering social, economic, organisational, environmental and technical concerns. In addition, the interdependence of the different modes of transport and the resulting human activities requires the inclusion of the spatial dimension to capture potential cascading failures. Furthermore, the integration of both aleatory (data) and epistemic (modelling) uncertainties is essential for robust performance indicators.

With increasing interdependencies and evolving threats, maintaining operational continuity in critical systems has become a significant challenge. This paper presents the DYNABIC (Dynamic business continuity of critical infrastructures on top of adaptive multi-level cybersecurity) approach as a comprehensive framework to enhance the resilience of critical infrastructures. The DYNABIC approach provides the resilience enhancement through dynamic adaptation, automated response, collaboration, risk assessment, and continuous improvement. By fostering a proactive and collaborative approach to resilience, the DYNABIC framework empowers critical infrastructure sectors to effectively mitigate disruptions and recover from incidents. The paper explores the key components and architecture of the DYNABIC approach and highlights its potential to strengthen the resilience of critical infrastructures using the concept of Digital Twins in the face of evolving threats and complex operating environments involving cascading effects.

International audience

The complexity of the Cyber-Physical Systems (CPS) and their interactions with the physical environment makes them difficult to model completely. Once deployed, these systems are therefore subject to unexpected events that may degrade their behavior. Consequently, it becomes necessary to evaluate, at runtime, the degree of effectiveness of these systems. To address this concern, a new approach is proposed, drawing its foundations from the possibility theory and accounting for temporal constraints. The degree of effectiveness is then given as the degree of possibility. A step further, the Choquet integral operator is used for aggregating multiple evaluations, providing us with a measure of the users' satisfaction w.r.t. their preferences. Finally the proposed approach is validated through a use-case in the smart-home domain.

Background. With the recent advent of the so-called connected objects, today largely present in our surroundings, software applications have an open door to the physical world through sensors and actuators. However, although it offers huge opportunities in many areas (e.g., smart-home, smart-cities, etc...), it poses a serious methodological challenge. Indeed, while classical software applications operate in the well known and delimited digital world, the so-called ambient applications operate in and through the physical world, open and subject to uncertainties that cannot be modeled accurately and entirely. These uncertainties lead the behavior of the ambient applications to potentially drift over time against requirements. In this paper, we propose a framework to estimate the behavioral drift of the ambient applications against requirements at runtime.