Cross-Border Threat Screening and Supply Chain Defense

A Department of Homeland Security Center of Excellence

Development of a Verifiable, Privacy-Controlled Medical Information Exchange Network –System Concept and Testbed

Issue:

Source-assured biomedical data (BMD) distribution is critical to medicine, public health, and biological threat research. Researchers need to have high confidence that the digital assets in hand are produced by vetted principals, and that the chains of data recombination and alteration, both intentional and unintentional, are traceable. The data owner should be assured of indisputable ownership amidst a very complex data distribution process, with confidence that principles found to violate the access protocol can be banned from further access to the digital asset(s) in question.

Objectives:

This project aims to develop the foundational system concept, basic system architecture, and system protocols for a next-generation medical and public health information network, the BMD Supply Chain (BMDSC). This system will support

  • verifiable, privacy-protected information inquiry and response between subjects, and
  • management of identifiers of subjects and their cryptographic credentials to engage in the information exchange. Capabilities will be built around
    • the W3C standards on Verifiable Credentials (VC), the scalable, immutable privacy-protected logging (SIPL) service developed through partnership between TAMU CBTS and TAMU Computer Science, and
    • the W3C standards on Decentralized Identifiers (DID).
Technical Illustration from Texas A&M University – College of Engineering - Computer Science

Value Proposition:

Data traceability, contribution/edit attribution, and verification/identification of data from disperse sources is all paramount in detection, response to, and synthesis of reliable operational awareness. Detection of current and yet undefined threats and associated conditions or syndromes, whether naturally occurring or synthetic in origin, remains a critical challenge for US medical and public health systems and for the populace. This project will apply a combination of best and emerging practices from the supply chain, medical informatics, and computer science domains to build a functioning testbed to allow trial and exercise of novel medical data aggregation and verification paradigms.

Project Lead Texas A&M University – College of Engineering – Computer Science
Research TeamPI: Steve Liu, Ph.D., TAMU Computer Science and Engineering Co-PI: Matt Cochran, DVM, CBTS
Budget$752,622
DurationApril 2023 – March 2025