TSU DHS SLA program involves faculty members, especially early career faculty across different departments to develop an interdisciplinary and integrated research and education program that provides innovative technology solutions for the Homeland Security Enterprise (HSE), particularly for maritime transportation security. Based on interviews with security officers in Houston Port of Houston Authority and the areas of expertise of early career faculty and other researchers at TSU, the following three research activities have been identified:
Despite mandates by the International Maritime Organization (IMO) and the U.S. Coast Guard to perform regular risk assessments at ports, on board ships, and at the office, to verify how incidents, accidents, injuries, or near misses are caused, companies are frequently reluctant or unable to identify potential risks, thus imposing a threat to their own systemic integrity. This project will examine the industry’s practices and the identification of systemic failures, with the purpose of significantly improving corporate risk management and risk-assessment practices. It will establish a systemic platform for the maritime industry by modeling and analyzing risk assessment and management. It will develop and validate the industry’s regulatory requirements and standards by employing established, measurable, and demonstrable measures that will improve the prevention and vulnerability reduction measurement in the shipping industry. The results of this research project will enhance the efficiency and functionality of the safeguard systems of the present maritime infrastructure.
Given the extensive economic importance of the maritime supply chain, the vulnerability of maritime cargo to smuggling, terrorist attacks, and other malicious attacks has long been a concern, especially after the events of 9/11. Since there are approximate 11.6 million maritime cargo security containers entering U.S. ports each year, an efficient screening model should be constructed and the U.S. Coast Guard needs effective tools to facilitate screening instead of the traditional screening by hand. This project will employ data mining techniques to create an intelligent screening model to strengthen maritime cargo security. Briefly, it will analyze the record data of cargo attributes (e.g., the ports of origin of cargo containers, the shipping company, crew information, the content of cargo containers, etc.), and employ this historical data as training data to build up a risk-based screening classifier. When new cargo containers enter port, the Coast Guard just needs to input some attributes of the cargo into its online portable devices (e.g., tablet, iPad, smart phones, etc.), assess the risk of the cargo, and single out high-risk cargo for further inspection. An intelligent screening model and software prototype will be developed in this project. The results of this research will provide an effective, efficient, and feasible approach to the screening of U.S.-bound cargo, which will enhance the security and prosperity of the maritime supply chain.
Due to the massive amount of maritime cargo containers entering U.S. ports, it costs too much to store all the cargo records in the servers at local ports (e.g., the cost of adding servers, data maintenance costs, the cost of server specialists, etc.). One way to effectively reduce these costs is to centralize all maritime data in large data centers, i.e., the cloud. Since maritime data are sensitive, this project will develop encryption schemes to maintain data integrity and ensure the data are immune to attack by malicious hackers. Meanwhile, since maritime data are frequently updated, stored, and retrieved, this project will also employ cryptography techniques to secure efficient data storage and retrieval. The attack model will be investigated, security analysis and complexity analysis will be conducted for the proposed schemes, and the results of this research will help to secure efficient maritime data storage and retrieval.