Digital Twins (DTs) are crucial uprising technologies within Industry 4.0, offering virtual representations dynamically for simulation, control, and real-time monitoring of physical systems. Their extensive integration with the Internet of Things (IoT) and Cyber-Physical Systems (CPS) results in major cybersecurity vulnerabilities, especially with regard to disruptive Denial of Service (DoS) attacks that endanger data integrity and operational continuity. This study methodically identifies and ranks the major causative factors of DoS cyber-attacks in digital twin systems. Applying an integrated Multi-Criteria Decision-Making (MCDM) technique, the Analytic Hierarchy Process (AHP) determines the weights of evaluation criteria on the basis of expert opinions, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) ranks the detected attack factors. The final outcomes claim missing redundancy and load balancing, a lack of traffic throttling or rate-limiting systems, and flooding via exposed interfaces as the most vital attack factors. The robustness of these rankings is confirmed by a systematic sensitivity analysis, which provides a proven prioritization to direct focused security measures for improving the cyber-resilience of digital twin systems.