An Integrated Model for Ranking Risk Management in Industrial Internet of Things (IIoT) system

Abstract

The Industrial Internet of Things (IIoT) was developed based on the technology and applications of the
Internet of Things (IoT) in an industrial environment. As it is a sub-set of the IoT, it requires higher levels
of safety and security. While increased productivity, better management and high operational efficiency
are its main goals, they involve managing many risks, such as conflicting criteria and uncertain
information, that need to be assessed and ranked. Therefore, in this paper, the Multi-criteria Decisionmaking (MCDM) method is used to deal with these criteria and a neutrosophic environment to overcome
the uncertainty. Also, the Analytical Hierarchical Process (AHP) and Technique for Order of Preference
by Similarity to Ideal Solution (TOPSIS) approaches are proposed. The former is used to obtain the
weights of the criteria and the latter to rank the management of risk in the IIOT system. Numerical
examples are provided and a sensitivity analysis conducted to test the reliability of this model.