Biblio

In Industrial Internet of Things (IIoT) scenarios, where a plethora of IoT technologies coexist with consolidated industrial infrastructures, the integration of security mechanisms that provide protection against cyber-security attacks becomes a critical challenge. Due to the stealthy and persistent nature of some of these attacks, such as Advanced Persistent Threats, it is crucial to go beyond traditional Intrusion Detection Systems for the traceability of these attacks. In this sense, Opinion Dynamics poses a novel approach for the correlation of anomalies, which has been successfully applied to other network security domains. In this paper, we aim to analyze its applicability in the IIoT from a technical point of view, by studying its deployment over different IIoT architectures and defining a common framework for the acquisition of data considering the computational constraints involved. The result is a beneficial insight that demonstrates the feasibility of this approach when applied to upcoming IIoT infrastructures.

Abstract Cyber-physical systems (CPSs), integrated in critical infrastructures, could provide the minimal services that traditional situational awareness (SA) systems demand. However, their application in SA solutions for the protection of large control distributions against unforeseen faults may be insufficient. Dynamic protection measures have to be provided not only to locally detect unplanned deviations but also to prevent, respond, and restore from these deviations. The provision of these services as an integral part of the SA brings about a new research field known as wide-area situational awareness (WASA), highly dependent on CPSs for control from anywhere across multiple interconnections, and at any time. Thus, we review the state-of-the art of this new paradigm, exploring the different preventive and corrective measures considering the heterogeneity of CPSs, resulting in a guideline for the construction of automated WASA systems.