# Pinocchio: Nearly Practical Verifiable Computation

@inproceedings{Parno2013PinocchioNP, title={Pinocchio: Nearly Practical Verifiable Computation}, author={Bryan Parno and Jon Howell and Craig Gentry and Mariana Raykova}, booktitle={IEEE Symposium on Security and Privacy}, year={2013} }

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…

## 305 Citations

Pinocchio : Nearly Practical Verifiable Computation

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This work proposes an efficient verification outsourcing scheme and shows that, without using expensive fully-homomorphic encryption, an honest-but-curious third party can help to verify the result of an outsourced computational task without having to learn either the computational task or the result thereof.

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This work advances a recent line of work on "proof systems" in which the service provider proves the correctness of its output to a user, and describes a set of techniques that achieve genuine scalability for protocols fine-tuned for specific important problems in streaming and database processing.

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This work presents the first certified, semantics-preserving compiler for verifiable computing, based on CompCert and developed in Coq, and targets an architecture whose instructions consist solely of quadratic equations over a large finite field, amenable to succinct verification using the Pinocchio cryptographic scheme.

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This work presents a scheme for verifiable evaluation of hierarchical set operations unions, intersections and set-differences applied to a collection of dynamically changing sets of elements from a given domain and concludes that the cost of updates is optimal involving O1 modular operations per update.

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