ZoKrates - Scalable Privacy-Preserving Off-Chain Computations

Scalability and privacy are two challenges for today's blockchain systems. Processing transactions at every node in the system limits the system's ability to scale. Furthermore, the requirement to publish all corporate or individual information for processing at every node, essentially making the data public, is - despite of all other advantages - often considered a major obstacle to blockchain adoption. In this paper, we make two main contributions to address these two problems: (i)To increase efficiency, we propose a processing model which employs noninteractive proofs to off-chain computations, thereby reducing on-chain computational efforts to the verification of correctness of execution rather than the execution itself. Due to the verifiable computation scheme's zero-knowledge property, private information used in the off-chain computation does not have to become public to verify correctness. (ii)We introduce ZoKrates, a toolbox to specify, integrate and deploy such off-chain computations. It consists of a domain-specific language, a compiler, and generators for proofs and verification Smart Contracts. ZoKrates hides significant complexity inherent to zero-knowledge proofs, provides a more familiar and higher level of programming abstractions to developers and enables circuit integration, hence fostering adoption.