Proactive Complex Security Analysis of IoT-Based Critical Infrastructure Facilities

This paper develops an approach for proactive, predictive and complex security analysis of critical infrastructure facilities, that are utilizing Internet of Things technologies (IoT-based CIFs). The study employs extrapolation algorithms and granular computing, which consider the noise present in initial data. This allows even in the uncertainties of data observation and measurement, to determine and predict important aspects of functioning of IoT-based CIFs. We believe that consideration of such knowledge can significantly contribute to the complex security of such systems. The main features of this approach are analyzed. The proposed approach enables proactive security assessment, determining acceptable thresholds for deviations from security requirements. Furthermore, by formalizing these metrics as deviations from security requirements, this approach enables the unification of proactive assessment algorithms. In turn, it opens a possibility for unifying monitoring, protection, and resource management algorithms of IoT-based CIFs.