"Marquette Computer Science Professor Receives NSF Funding for Confidential Computing Solutions"
Dr. Keke Chen, Northwestern Mutual Data Science Institute Associate Professor of Computer Science at Marquette University's Klingler College of Arts and Sciences, has been awarded a $600,000 National Science Foundation (NSF) grant to explore confidential computing solutions in scientific collaboration. NSF's Cybersecurity Innovation for Cyberinfrastructure (CICI) program funded Chen's research project, "Confidential Computing in Reproducible Collaborative Workflows." NSF CICI supports research on scientific data, workflows, and infrastructure security in three areas, including usable and collaborative security for science, reference scientific security datasets, and the discovery of scientific infrastructure vulnerabilities. According to Chen, data-intensive scientific research projects typically involve multiple collaborative parties, each of which may require confidential processing of their sensitive assets to protect intellectual property, embargoed data, and algorithm sharing before publishing a paper. Integrating confidential computing into reproducible scientific workflows presents significant but understudied challenges. The goal of Chen's project is to identify these unique challenges and research novel solutions. This research will concentrate on the efficient hardware-based confidential computing approach, known as the Trusted Execution Environment (TEE), for scientific data analytics applications. Researchers will explore solutions for scientist-oriented TEE development that balance usability and security guarantees. They will also look at unique attacks resulting from the interaction between confidential components and a reproducible workflow, with the goal of developing mitigation methods based on the attack research to ensure workflow reproducibility and security. This article continues to discuss the support, goals, and areas of focus behind the "Confidential Computing in Reproducible Collaborative Workflows" research project.