Traditionally, confidentiality and integrity have been two desirable design goals that are have been dicult to combine. Zero-Knowledge Proofs of Knowledge (ZKPK) offer a rigorous set of cryptographic mechanisms to balance these concerns. However, published uses of ZKPK have been dicult for regular developers to integrate into their code and, on top of that, have not been demonstrated to scale as required by most realistic applications.

This paper presents ZØ (pronounced “zee-not”), a compiler that consumes applications written in C# into code that automatically produces scalable zeroknowledge proofs of knowledge, while automatically splitting applications into distributed multi-tier code. ZØ builds detailed cost models and uses two existing zeroknowledge back-ends with varying performance characteristics to select the most ecient translation. Our case studies have been directly inspired by existing sophisticated widely-deployed commercial products that require both privacy and integrity. The performance delivered by ZØ is as much as 40 faster across six complex applications. We find that when applications are scaled to real-world settings, existing zero-knowledge compilers often produce code that fails to run or even compile in a reasonable amount of time. In these cases, ZØ is the only solution we know about that is able to provide an application that works at scale.