LAUSR

Context: Denial-of-Service Attack countermeasure techniques (DoS A-CTs) evaluation is a Multi-criteria decision-making (MCDM) problem based on different MPSoCs of IoT platform design, performance, and design overhead. Therefore, the Fermatean by fuzzy decision opinion score method (F-FDOSM) for prioritizing the powerful countermeasure technique against Denial-of-Service (DoS) attack is the best approach because it employs the most efficient MCDM ranking technique. Nonetheless, the FDOSM method needs to weight the criteria before being submitted for the ranking process. In order to address this theoretical challenge, the Criteria-importance through inter-criteria correlation (CRITIC) technique can be applied as an effective MCDM weighting technique to offer an explicit weight for a set of criteria with no inconsistency based on the standard deviation, which uses correlation analysis to determine the relevance of each criterion. Objectives: This research proposes a Fermatean-FDOSM framework for evaluating DoS A-CTs in the context of MPSoCs-based IoT and CRITIC techniques to weight the criteria. Methods: The methodology is presented in three phases. Firstly, a proposed countermeasure techniques dataset was collected that included eighteen defense approaches (e.g., Sniffer, SeRA, and RLAN) based on thirteen criteria (e.g., size, power, latency, and effectiveness…etc.). Then, the Decision matrix (DM) was built based on an intersection of the countermeasure techniques as an alternative and MPSoC design and performance criteria. Then, the multi-criteria decision-making methods were integrated. The CRITIC method for criteria weighting was followed by the development of the Fermatean-FDOSM method for ranking. Results: (1) CRITIC weighting shows that MPSoC NoC Routing Algorithm (XY and YX) is the highest weight criterion, whereas latency (clock/cycle) is the less weight criterion. (2) The Fermatean-FDOSM-based group ranking shows that the Collision Point Router Detection (CPRD) countermeasure technique is the first-ranked alternative compared to the Secure Model Checkers (SMCs) approach. (3) The DoS A-CTs priority ranks were subjected to a systematic ranking that was confirmed by solid correlation results throughout thirteen criterion weight values. A comparison with recent studies confirmed the feasibility of the proposed framework. Conclusion: The results of this research are expected to provide a specific understanding and guide for those who want to engage in MPSoCs-based IoT and NoC communication security research with decision theory.