22.12.2022
Privacy-preserving Automated Reasoning
Bugs in software and hardware can often to catastrophic consequences. There are various ways to improve software quality, formal verification being the most rigorous of all. In formal verification, the goal is to translate programs into formulas, and then automatically prove the correctness of these formulas. Formal methods offer a vast collection of techniques to analyze and verify these systems mathematically to ensure the correctness, robustness, and safety of software and hardware systems against a specification. Despite the significant success of formal method techniques, privacy requirements are not considered in their design.
In the last two decades, we have witnessed fascinating progress in the area of automated reasoning. Modern automated reasoning tools are now applied daily to tasks in program analysis, software engineering, hardware verification, and various other domains. The efficacy of such tools allows their application to even large-scale industrial codebases.
In this talk, we will present our work on adding a privacy-aware perspective to automated reasoning. When using automated reasoning tools, the implicit requirement is that the formula to be proved is public. We propose the concept of privacy-preserving formal reasoning. In our recent work on a zero-knowledge protocol for proving the unsatisfiability of Boolean formulas in propositional logic, we developed a highly efficient protocol for knowledge of a resolution proof of unsatisfiability. We encoded verification of the resolution proof using polynomial equivalence checking, which enabled us to use fast ZKP protocols for polynomial satisfiability.
BIO: Ruzica Piskac is an associate professor of computer science at Yale University. Her research interests span the areas of programming languages, software verification, automated reasoning, and code synthesis. A common thread in Ruzica’s research is improving software reliability and trustworthiness using formal techniques. Ruzica joined Yale in 2013 as an assistant professor and professor, and prior to that, she was an independent research group leader at the Max Planck Institute for Software Systems in Germany. In July 2019, she was named the Donna L. Dubinsky Associate Professor of Computer Science, one of the highest recognitions that an untenured faculty member at Yale can receive. Ruzica has received various recognitions for research and teaching, including the Patrick Denantes Prize for her PhD thesis, a CACM Research Highlight paper, an NSF CAREER award, the Facebook Communications and Networking award, the Microsoft Research Award for the Software Engineering Innovation Foundation (SEIF), the Amazon Research Award, and the 2019 Ackerman Award for Teaching and Mentoring.
BIO: Ruzica Piskac is an associate professor of computer science at Yale University. Her research interests span the areas of programming languages, software verification, automated reasoning, and code synthesis. A common thread in Ruzica’s research is improving software reliability and trustworthiness using formal techniques. Ruzica joined Yale in 2013 as an assistant professor and professor, and prior to that, she was an independent research group leader at the Max Planck Institute for Software Systems in Germany. In July 2019, she was named the Donna L. Dubinsky Associate Professor of Computer Science, one of the highest recognitions that an untenured faculty member at Yale can receive. Ruzica has received various recognitions for research and teaching, including the Patrick Denantes Prize for her PhD thesis, a CACM Research Highlight paper, an NSF CAREER award, the Facebook Communications and Networking award, the Microsoft Research Award for the Software Engineering Innovation Foundation (SEIF), the Amazon Research Award, and the 2019 Ackerman Award for Teaching and Mentoring.