A Comparative Analysis of zk-SNARKs and zk-STARKs: Theory and Practice
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866914193724145664 |
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| author | Nainwal, Ayush Kamble, Atharva Awathare, Nitin |
| author_facet | Nainwal, Ayush Kamble, Atharva Awathare, Nitin |
| contents | Zero-knowledge proofs (ZKPs) are central to secure and privacy-preserving computation, with zk-SNARKs and zk-STARKs emerging as leading frameworks offering distinct trade-offs in efficiency, scalability, and trust assumptions. While their theoretical foundations are well studied, practical performance under real-world conditions remains less understood.
In this work, we present a systematic, implementation-level comparison of zk-SNARKs (Groth16) and zk-STARKs using publicly available reference implementations on a consumer-grade ARM platform. Our empirical evaluation covers proof generation time, verification latency, proof size, and CPU profiling. Results show that zk-SNARKs generate proofs 68x faster with 123x smaller proof size, but verify slower and require trusted setup, whereas zk-STARKs, despite larger proofs and slower generation, verify faster and remain transparent and post-quantum secure. Profiling further identifies distinct computational bottlenecks across the two systems, underscoring how execution models and implementation details significantly affect real-world performance. These findings provide actionable insights for developers, protocol designers, and researchers in selecting and optimizing proof systems for applications such as privacy-preserving transactions, verifiable computation, and scalable rollups. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_10020 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Comparative Analysis of zk-SNARKs and zk-STARKs: Theory and Practice Nainwal, Ayush Kamble, Atharva Awathare, Nitin Cryptography and Security Distributed, Parallel, and Cluster Computing Zero-knowledge proofs (ZKPs) are central to secure and privacy-preserving computation, with zk-SNARKs and zk-STARKs emerging as leading frameworks offering distinct trade-offs in efficiency, scalability, and trust assumptions. While their theoretical foundations are well studied, practical performance under real-world conditions remains less understood. In this work, we present a systematic, implementation-level comparison of zk-SNARKs (Groth16) and zk-STARKs using publicly available reference implementations on a consumer-grade ARM platform. Our empirical evaluation covers proof generation time, verification latency, proof size, and CPU profiling. Results show that zk-SNARKs generate proofs 68x faster with 123x smaller proof size, but verify slower and require trusted setup, whereas zk-STARKs, despite larger proofs and slower generation, verify faster and remain transparent and post-quantum secure. Profiling further identifies distinct computational bottlenecks across the two systems, underscoring how execution models and implementation details significantly affect real-world performance. These findings provide actionable insights for developers, protocol designers, and researchers in selecting and optimizing proof systems for applications such as privacy-preserving transactions, verifiable computation, and scalable rollups. |
| title | A Comparative Analysis of zk-SNARKs and zk-STARKs: Theory and Practice |
| topic | Cryptography and Security Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2512.10020 |