A Review of zk-SNARKs
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Abstract (arXiv)
A zk-SNARK is a protocol that lets one party, the prover, prove to another party, the verifier, that a statement about some privately-held information is true without revealing the information itself. This paper describes technical foundations, current applications, and some novel applications of zk-SNARKs. Regarding technical foundations, we go over the Quadratic Arithmetic Program reduction and the Pinocchio protocol. We then go over financial security applications like Zcash and Tornado Cash, and zk-Rollup applications like zkEVM and Darkforest. We propose novel zk-SNARK protocols for private auctions and decentralized card games on the blockchain, providing code for the proposed applications. We conclude by touching on promising zk-SNARK innovations, such as zk-STARKs.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Feb 2022.
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Citing papers per year: 2023: 1; 2024: 3; 2025: 3; 2026: 1.
8 papers.
- 2026Autonomous Agents on Blockchains: Standards, Execution Models, and Trust Boundariescited by 12
- 2024Towards Secure and Private AI: A Framework for Decentralized Inferencecited by 1
- 2023Hashmarks: Privacy-Preserving Benchmarks for High-Stakes AI Evaluationcited by 0
- 2024Privacy-Preserving UCB Decision Process Verification via zk-SNARKscited by 0
- 2024Fractal Signatures: Securing AI-Generated Pollock-Style Art via Intrinsic Watermarking and Blockchaincited by 0
- 2025Verifiable Split Learning via zk-SNARKscited by 0
- 2025Knowledge is Overrated: A zero-knowledge machine learning and cryptographic hashing-based framework for verifiable, low latency inference at the LHCcited by 0
- 2025Trustless Federated Learning at Edge-Scale: A Compositional Architecture for Decentralized, Verifiable, and Incentive-Aligned Coordinationcited by 0
- 2026Autonomous Agents on Blockchains: Standards, Execution Models, and Trust Boundaries8 Jan 2026
- 2025Trustless Federated Learning at Edge-Scale: A Compositional Architecture for Decentralized, Verifiable, and Incentive-Aligned Coordination26 Nov 2025
- 2025Knowledge is Overrated: A zero-knowledge machine learning and cryptographic hashing-based framework for verifiable, low latency inference at the LHC16 Nov 2025
- 2025Verifiable Split Learning via zk-SNARKs3 Nov 2025
- 2024Fractal Signatures: Securing AI-Generated Pollock-Style Art via Intrinsic Watermarking and Blockchain27 Oct 2024
- 2024Towards Secure and Private AI: A Framework for Decentralized Inference28 Jul 2024
- 2024Privacy-Preserving UCB Decision Process Verification via zk-SNARKs18 Apr 2024
- 2023Hashmarks: Privacy-Preserving Benchmarks for High-Stakes AI Evaluation1 Dec 2023