A Survey on the Applications of Zero-Knowledge Proofs
Ryan Lavin, Xuekai Liu, Hardhik Mohanty, Logan Norman, Giovanni Zaarour, Bhaskar Krishnamachari
TL;DR
Zero-knowledge proofs (ZKPs) enable verifiable computations without exposing underlying data, offering succinctness and strong privacy advantages over alternatives like homomorphic encryption and secure multi-party computation. The paper provides a comprehensive, application-focused survey of zkSNARKs, zkVMs, zk-DSLs, and supporting tools, detailing their roles across blockchain layers (L1/L2), interoperability, storage, identity, supply chains, and non-blockchain domains such as ML and voting. It clarifies the SNARK lifecycle ( Frontends, Arithmetization, Backends ) and the infrastructure enabling practical deployment (PCSs, trusted ceremonies, Fiat-Shamir), while highlighting hardware accelerators and libraries that drive performance. By mapping concrete use-cases (e.g., zkEVM rollups, privacy-preserving identities, ZK-PoR, and private ML proofs) and identifying gaps, the survey outlines actionable directions for researchers and practitioners to advance privacy-preserving verifiable computation at scale.
Abstract
Zero-knowledge proofs (ZKPs) represent a revolutionary advance in computational integrity and privacy technology, enabling the secure and private exchange of information without revealing underlying private data. ZKPs have unique advantages in terms of universality and minimal security assumptions when compared to other privacy-sensitive computational methods for distributed systems, such as homomorphic encryption and secure multiparty computation. Their application spans multiple domains, from enhancing privacy in blockchain to facilitating confidential verification of computational tasks. This survey starts with a high-level overview of the technical workings of ZKPs with a focus on an increasingly relevant subset of ZKPs called zk-SNARKS. While there have been prior surveys on the algorithmic and theoretical aspects of ZKPs, our work is distinguished by providing a broader view of practical aspects and describing many recently-developed use cases of ZKPs across various domains. These application domains span blockchain privacy, scaling, storage, and interoperability, as well as non-blockchain applications like voting, authentication, timelocks, and machine learning. Aimed at both practitioners and researchers, the survey also covers foundational components and infrastructure such as zero-knowledge virtual machines (zkVM), domain-specific languages (DSLs), supporting libraries, frameworks, and protocols. We conclude with a discussion on future directions, positioning ZKPs as pivotal in the advancement of cryptographic practices and digital privacy across many applications.