This EArly-concept Grant for Exploratory Research (EAGER) will contribute to the advancement of national prosperity and economic welfare by studying how illicit supply chain networks operate, and in particular when using the processes and practices of legal networks. Identifying the ways in which counterfeiting and other fraudulent parties operate will help redress this multi-billion-dollar drain on the US economy, which results in both loss of income for the affected legitimate parties and loss of tax income for the US government. Counterfeit goods supply chains take advantage of legitimate distribution networks but are discoverable because their transactional signatures are different from those of legal transactions. This project involves comparing the analytics collected for both physical inventory and cyber activity to determine the patterns of illicit activities that distinguish them from those of lawful trade. These patterns arise from sales figures, labor analytics, and differences from expected reported trade values in time and locations. By effectively characterizing suspicious digital transactions and better distinguishing between legitimate and illegitimate enterprises, this research will lead to more effective countermeasures in the digital space used by the majority of commercial enterprises. The project team involve cross-disciplinary expertise in computer science, operations engineering, and forensic materials science, and will provide opportunities for graduate students in this multi-faceted effort.
This project will provide the multi-tiered cyber-physical processes for statistical-based discovery of illicit activities and their enabling illicit networks. The starting point is determining statistically relevant deviations from the licit supply chains that illicit trade is dependent on for efficiency and for simulating legitimacy. Physical and cyber forensic processes will be investigated and compared: hybrid machine learning and analytics of public information such as web sales and product pricing sites, and privileged information such as projected and realized regional and seasonal sales, allow the analytics to identify the most salient threat surface points in the illicit supply chains. Fundamental understanding of the operations of illicit networks - to explore, expose and exploit their vulnerabilities - involves the collection of evidence to lead back to the source. In the physical space, this project will investigate the use of an imaging-fueled forensic service (IFFS) tied to fast-onramp sources of information (returns centers, secret shopping, online activity) and capable of determining compliance with serialization, copy prevention, and anti-tamper. These physical forensics are used to provide "independent accounting" for the on-line analytics focused on sales, pricing, and supply chain analytics. Based on indications of illicit activity, the project will evaluate means to steer potentially illicit users into revealing themselves as non-legitimate based on their ability to reproduce the legitimate supply chain.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.