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Athletics Arts & Culture Campus & Community People Research
Athletics Arts & Culture Campus & Community People Research

NSF Award Funds Research in Privacy-Protecting Computing

Two University of Maryland programming and cryptography experts have received nearly $600,000 from the National Science Foundation to study how programming languages can be used to make computing more secure.

The three-year award supports the work of Leonidas Lampropoulos and Ian Miers, both assistant professors of computer science with appointments in the University of Maryland Institute for Advanced Computer Studies. Both are also core members of the Maryland Cybersecurity Center (MC2).

They are collaborating with Ethan Cecchetti, a former MC2 postdoctoral researcher now at the University of Wisconsin–Madison, and are also being assisted by UMD computer science doctoral student Oliwia Kempinski.

The research focuses on non-interactive zero-knowledge proofs (NIZKs), which are cryptographic tools that can be easily checked to prove information is correct without revealing the information itself. Recent advances have made NIZKs a promising tool for verifying computations, protecting privacy and supporting machine learning.

Currently, most NIZK systems are built as one-offs, making them harder to use and maintain. The UMD/University of Wisconsin–Madison team aims to change that by developing programming tools and structures that make NIZKs easier for developers to use and improve the quality of software they’re building.

The project will tackle three main challenges: combining code that generates NIZK proofs with code that verifies them; using information flow control to describe the security guarantees of NIZKs; and exploring ways to write security rules for real-world applications, allowing end-to-end verification of systems like anonymous credential platforms and private payment systems with anti-money laundering protections.

By moving beyond one-off designs, the researchers hope to make NIZKs more practical for developers and open the door to more privacy-protecting applications, benefiting industries such as finance, health care and others that rely on sensitive data.