Cognitive Cybersecurity in Transportation 5.0 and Supply Chain: A Multi-Objective Optimization Framework

This research introduces an innovative strategy to bolster cybersecurity within Transportation 5.0 and Supply Chain realms via a Multi-Objective Identification and Optimization Framework. Specifically crafted to tackle the intricate challenges posed by a mixed-integer non-linear problem (MINLP), this framework employs post-linearization techniques. Its primary aim is to strike a balanced trade-off between cyber risk and investment, crucial for fortifying the integrity and resilience of modern transportation and supply chain systems. The model serves as a tool for effective decision-making by evaluating supplier susceptibility (nodes), strategically mitigating vulnerabilities, and optimizing the alignment of categorized factors. Leveraging multi-objective optimization, this framework empowers decision-makers to navigate the complex cybersecurity landscape and allocate resources optimally. This comprehensive approach ensures a robust defense against evolving cyber threats within the dynamic domains of Transportation 5.0 and Supply Chain.