Data Driven Optimization of Port Centric Maritime Logistics and Containerized Supply Chains to Improve Transportation Efficiency and Economic Performance in the United States

The proliferation of cloud-native architectures, including microservices, allows organisations to build and deploy enterprise applications at unprecedented speed and scale. APIs provide the basis for the distributed application environment by enabling communications between multiple applications (service) and users, and multiple organisations and partners. However, as the number of APIs increases, they will result in significant increases in the attack surface available to attackers, including credential theft and abuse, data infiltration, distributed denial of service (DoS), and advanced persistent threats (APTs). As a result of this, traditional security models that are confined to the perimeter and static API management solutions will become less effective in a continually changing, highly dynamic and decentralised environment. This research proposes an intelligent and secure framework for API governance that combines the security principles of Zero Trust with AI-based anomaly detection for microservices (enterprise) ecosystems. This governance framework employs continuous authentication, fine-grained authorisation, behaviour analysis and real-time monitoring to ensure adaptive and proactive API protection. The layered governance model created in this study has been created using both conceptual and analytical methodologies and is aligned with business objectives, regulatory compliance and operational resiliency. Zero Trust-based API governance significantly increases the accuracy of detecting potential threats and decreases the time to respond.