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.