Enhancing Vessel Operational Safety and Security: A Cross-Layer Data Fusion Framework for Real-Time Maritime Anomaly Monitoring

Title : Data and Code for: Enhancing Vessel Operational Safety and Security: A Cross-Layer Data Fusion Framework for Real-Time Maritime Anomaly Monitoring Description : This dataset and reproducibility package support the research presented in the manuscript titled "Enhancing Vessel Operational Safety and Security: A Cross-Layer Data Fusion Framework for Real-Time Maritime Anomaly Monitoring" submitted to Ships and Offshore Structures. To comply with open data sharing policies while maintaining maritime operational security and confidentiality, this package provides a set of scenario-based synthetic datasets. These datasets were generated using rigorous engineering parameters to simulate real-world maritime anomalies, including: Illegal Oil Discharge (Case 1) AIS Spoofing Detection (Case 2) Night-time Ship-to-Ship (STS) Transfer (Case 3) Grounding Risk and Route Deviation (Case 4) Package Contents: generate_hml_dataset.py: The Python script used to generate the synthetic data based on physical and communication models (e.g., Haversine formula, satellite/UAV delay models). parameters.json: A configuration file containing the engineering assumptions and threshold values used in the simulations. CSV Files (Case 1–4): The resulting synthetic datasets used for the analysis and visualization within the manuscript. README.txt: Documentation explaining the data structure and how to run the scripts. By providing these materials, the authors ensure the reproducibility of the proposed Cross-Layer Data Fusion Framework and the validation of its anomaly monitoring capabilities.