Biblio

 The notion of controllability, informally the ability to force a system into a desired state in a finite time or number of steps, is most closely associated with control systems such as those used to maintain power networks and other critical infrastructures, but has wider relevance in distributed systems. It is clearly highly desirable to understand under which conditions attackers may be able to disrupt legitimate control, or to force overriding controllability themselves. Following recent results by Liu et al., there has been considerable interest also in graph-theoretical interpretation of Kalman controllability originally introduced by Lin, structural controllability. This permits the identification of sets of driver nodes with the desired state-forcing property, but determining such nodes is aW[2]-hard problem. To extract these nodes and represent the control relation, here we apply the POWER DOMINATING SET problem and investigate the effects of targeted iterative multiple-vertex removal. We report the impact that different attack strategies with multiple edge and vertex removal will have, based on underlying non-complete graphs, with an emphasis on power-law random graphs with different degree sequences.

The extraordinary growth of the Information Society is originating a high dependency on ICT. This provokes that those strongly interrelated technological infrastructures, as well as the information systems that underpin them, become highly critical, since their disruption would lead to high economical, material and, sometimes, human loss. As a consequence, the protection of these Critical Information Infrastructures is becoming a major objective for governments and companies. In this paper, we give an overview of the main challenges and open research issues on Critical Information Infrastructure security, and introduce an on-going research project that, using wireless sensor networks as an underlying technology, is dealing with those problems. Our research project focuses on the development of protection, control, evaluation, maintenance and verification mechanisms, integrated into a secure service-oriented architecture.

The problem of controllability of networks arises in a number of different domains, including in critical infrastructure systems where control must be maintained continuously. Recent work by Liu et al. has renewed interest in the seminal work by Lin on structural controllability, providing a graph-theoretical interpretation. This allows the identification of driver nodes capable of forcing the system into a desired state, which implies an obvious target for attackers wishing to disrupt the network control. Several methods for identifying driver nodes exist, but require undesirable computational complexity. In this paper, we therefore investigate the ability to regain or maintain controllability in the presence of adversaries able to remove vertices and implicit edges of the controllability graph. For this we rely on the POWER DOMINATING SET (PDS) formulation for identifying the control structure and study different attack strategies for multiple network models. As the construction of a PDS for a given graph is not unique, we further investigate different strategies for PDS construction, and provide a simulative evaluation.

The class of Trustworthy Autonomous Systems (TAS) includes cyber-physical systems leveraging on self-x technologies that make them capable to learn, adapt to changes, and reason under uncertainties in possibly critical applications and evolving environments. In the last decade, there has been a growing interest in enabling artificial intelligence technologies, such as advanced machine learning, new threats, such as adversarial attacks, and certification challenges, due to the lack of sufficient explainability. However, in order to be trustworthy, those systems also need to be dependable, secure, and resilient according to well-established taxonomies, methodologies, and tools. Therefore, several aspects need to be addressed for TAS, ranging from proper taxonomic classification to the identification of research opportunities and challenges. Given such a context, in this paper address relevant taxonomies and research perspectives in the field of TAS. We start from basic definitions and move towards future perspectives, regulations, and emerging technologies supporting development and operation of TAS.