Risk-Based Cybersecurity Threat Prioritization in Digital Twin-Enabled Cyber-Physical Systems

Digital Twin (DT)-enabled cyber-physical systems (CPS) face cybersecurity risks due to their complex connections and high levels of interdependence. Traditional methods, for assessing risk often fail to rank these threats. This is especially true when expert opinions include ambiguity, uncertainty or unclear information. A Type 2 Neutrosophic Entropy– Measurement of Alternatives and Ranking according to COmpromise Solution (Entropy- MARCOS) framework for cybersecurity threat prioritization in DT-enabled CPS is proposed in this paper. The uncertainty and indeterminacy present in expert evaluations are represented by Type 2 Neutrosophic Numbers (T2NNs). While the MARCOS technique is used to assess and rank cybersecurity threats according to their relative utility with respect to ideal and anti-ideal solutions, the Entropy method is used to extract objective criterion weights from the decision matrix. Six criteria, including cybersecurity-specific and Digital Twin-related characteristics, are used to evaluate five cybersecurity threats: Man-in-the-Middle (MITM) attacks, Distributed Denial-of-Service (DDoS) attacks, data spoofing, assaults targeting the Digital Twin, and zero-day exploits. The results show that Man-in-the-Middle (MITM) attacks (A1) are ranked second, after zero-day exploits (A5). Despite changes in the relative placements of the other dangers, the sensitivity analysis shows that A5 continues to be the most dangerous threat across all studied variations in the weight provided to the Damage criterion. Additionally, the comparison with Simple Additive Weighting (SAW) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) shows that SAW produces a ranking identical to that of MARCOS (ρ = 1.00), while TOPSIS differs only by swapping the third and fourth positions (ρ = 0.90 with both methods). All three methods agree on the first (A5), second (A1), and last (A3) positions, indicating strong agreement among the ranking outcomes. In Digital Twin-enabled CPS inside Industry 4.0 contexts, the suggested framework offers an organized and data-driven method for ranking cybersecurity hazards and assisting with cybersecurity risk management.