Pinocchio: Nearly practical verifiable computation. To instill greater confidence in computations outsourced to the cloud, clients should be able to verify the correctness of the results returned. To this end, we introduce Pinocchio, a built system for efficiently verifying general computations while relying only on cryptographic assumptions. With Pinocchio, the client creates a public evaluation key to describe her computation; this setup is proportional to evaluating the computation once. The worker then evaluates the computation on a particular input and uses the evaluation key to produce a proof of correctness. The proof is only 288 bytes, regardless of the computation performed or the size of the inputs and outputs. Anyone can use a public verification key to check the proof. Crucially, our evaluation on seven applications demonstrates that Pinocchio is efficient in practice too. Pinocchio’s verification time is typically 10ms: 5-7 orders of magnitude less than previous work; indeed Pinocchio is the first general-purpose system to demonstrate verification cheaper than native execution (for some apps). Pinocchio also reduces the worker’s proof effort by an additional 19-60x. As an additional feature, Pinocchio generalizes to zero-knowledge proofs at a negligible cost over the base protocol. Finally, to aid development, Pinocchio provides an end-to-end toolchain that compiles a subset of C into programs that implement the verifiable computation protocol.

References in zbMATH (referenced in 40 articles )

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  1. Abdolmaleki, Behzad; Lipmaa, Helger; Siim, Janno; Zając, Michał: On subversion-resistant SNARKs (2021)
  2. Gvili, Yaron; Ha, Julie; Scheffler, Sarah; Varia, Mayank; Yang, Ziling; Zhang, Xinyuan: TurboIKOS: improved non-interactive zero knowledge and post-quantum signatures (2021)
  3. Kovalchuk, L.; Oliynykov, R.; Rodinko, M.: Security of the Poseidon hash function against non-binary differential and linear attacks (2021)
  4. Wang, Hailong; Deng, Yi; Xie, Xiang: Public verifiable private decision tree prediction (2021)
  5. Zhang, Liang Feng: Multi-server verifiable delegation of computations: unconditional security and practical efficiency (2021)
  6. Pinto, Alexandre Miranda: An introduction to the use of zk-SNARKs in blockchains (2020)
  7. Zhang, Liang Feng; Safavi-Naini, Reihaneh: Protecting data privacy in publicly verifiable delegation of matrix and polynomial functions (2020)
  8. Zhang, Liang Feng; Safavi-Naini, Reihaneh: Privacy-preserving verifiable delegation of polynomial and matrix functions (2020)
  9. Ben-Sasson, Eli; Chiesa, Alessandro; Riabzev, Michael; Spooner, Nicholas; Virza, Madars; Ward, Nicholas P.: Aurora: transparent succinct arguments for R1CS (2019)
  10. Kraiem, Firas; Isobe, Shuji; Koizumi, Eisuke; Shizuya, Hiroki: On the classification of knowledge-of-exponent assumptions in cyclic groups (2019)
  11. Luo, Fucai; Wang, Fuqun; Wang, Kunpeng; Chen, Kefei: A more efficient leveled strongly-unforgeable fully homomorphic signature scheme (2019)
  12. Xie, Tiacheng; Zhang, Jiaheng; Zhang, Yupeng; Papamanthou, Charalampos; Song, Dawn: Libra: succinct zero-knowledge proofs with optimal prover computation (2019)
  13. Zhang, Xiaoyu; Jiang, Tao; Li, Kuan-Ching; Castiglione, Aniello; Chen, Xiaofeng: New publicly verifiable computation for batch matrix multiplication (2019)
  14. Anisimov, A. V.; Novokshonov, A. K.: Trusted computing with addition machines. II (2018)
  15. Dumas, Jean-Guillaume: Proof-of-work certificates that can be efficiently computed in the cloud (invited talk) (2018)
  16. Ferretti, Luca; Marchetti, Mirco; Andreolini, Mauro; Colajanni, Michele: A symmetric cryptographic scheme for data integrity verification in cloud databases (2018)
  17. Liu, Jia; Jager, Tibor; Kakvi, Saqib A.; Warinschi, Bogdan: How to build time-lock encryption (2018)
  18. Alabdulatif, Abdulatif; Kumarage, Heshan; Khalil, Ibrahim; Yi, Xun: Privacy-preserving anomaly detection in cloud with lightweight homomorphic encryption (2017)
  19. Ben-Sasson, Eli; Bentov, Iddo; Chiesa, Alessandro; Gabizon, Ariel; Genkin, Daniel; Hamilis, Matan; Pergament, Evgenya; Riabzev, Michael; Silberstein, Mark; Tromer, Eran; Virza, Madars: Computational integrity with a public random string from quasi-linear PCPs (2017)
  20. Ben-Sasson, Eli; Chiesa, Alessandro; Tromer, Eran; Virza, Madars: Scalable zero knowledge via cycles of elliptic curves (2017)

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