Verifying computations with state

Braun, Benjamin; Feldman, Ariel J.; Ren, Zuocheng; Setty, Srinath; Blumberg, Andrew J.; Walfish, Michael

doi:10.1145/2517349.2522733

Cited by 121 publications

(120 citation statements)

References 72 publications

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“…Similar to above, this technique is efficient for some special cases, but not when used for general computation. In Section 6.2 we show that using our system results in more than 4 orders of magnitude better performance at the contractor side compared to employing Pantry [10] verifiable computation (one of the state of the art in verifiable computation). See [59] for a survey of such techniques.…”

Section: Related Workmentioning

confidence: 96%

Incentivized Outsourced Computation Resistant to Malicious Contractors

Küpçü

2017

IEEE Trans. Dependable and Secure Comput.

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With the rise of Internet computing, outsourcing difficult computational tasks became an important need. Yet, once the computation is outsourced, the job owner loses control, and hence it is crucial to provide guarantees against malicious actions of the contractors involved. Cryptographers have an almost perfect solution, called fully homomorphic encryption, to this problem. This solution hides both the job itself and any inputs to it from the contractors, while still enabling them to perform the necessary computation over the encrypted data. This is a very strong security guarantee, but the current constructions are highly impractical.In this paper, we propose a different approach to outsourcing computational tasks. We are not concerned with hiding the job or the data, but our main task is to ensure that the job is computed correctly. We also observe that not all contractors are malicious; rather, majority are rational. Thus, our approach brings together elements from cryptography, as well as game theory and mechanism design. We achieve the following results: (1) We incentivize all the rational contractors to perform the outsourced job correctly, (2) we guarantee high fraction (e.g., 99.9%) of correct results even in the existence of a relatively large fraction (e.g., 33%) of malicious irrational contractors in the system, (3) and we show that our system achieves these while being almost as efficient as running the job locally (e.g., with only 3% overhead). Such a high correctness guarantee was not known to be achieved with such efficiency.

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Section: Related Workmentioning

confidence: 96%

Incentivized Outsourced Computation Resistant to Malicious Contractors

Küpçü

2017

IEEE Trans. Dependable and Secure Comput.

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“…Essentially, support for non-deterministic reductions means that, unlike interactive proofs, the argument systems developed by Parno et al, Setty et al, and BenSasson et al can be run on non-deterministic circuits -i.e., circuits that "take advice" -without the prover having to explicitly send the advice inputs to the verifier. Very recent implementation work by Braun et al also exploits the ability of these argument systems to support circuits that take advice [20].…”

Section: Comparison With Other Approachesmentioning

confidence: 99%

Practical verified computation with streaming interactive proofs

Cormode

Mitzenmacher

Thaler

2012

Proceedings of the 3rd Innovations in Theoretical Computer Science Conference

153

269

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When delegating computation to a service provider, as in the cloud computing paradigm, we seek some reassurance that the output is correct and complete. Yet recomputing the output as a check is inefficient and expensive, and it may not even be feasible to store all the data locally. We are therefore interested in what can be validated by a streaming (sublinear space) user, who cannot store the full input, or perform the full computation herself. Our aim in this work is to advance a recent line of work on "proof systems" in which the service provider proves the correctness of its output to a user. The goal is to minimize the time and space costs of both parties in generating and checking the proof. Only very recently have there been attempts to implement such proof systems, and thus far these have been quite limited in functionality.Here, our approach is two-fold. First, we describe a carefully chosen instantiation of one of the most efficient general-purpose constructions for arbitrary computations (streaming or otherwise), due to Goldwasser, Kalai, and Rothblum [19]. This requires several new insights and enhancements to move the methodology from a theoretical result to a practical possibility. Our main contribution is in achieving a prover that runs in time O(S(n) log S(n)), where S(n) is the size of an arithmetic circuit computing the function of interest; this compares favorably to the poly(S(n)) runtime for the prover promised in [19]. Our experimental results demonstrate that a practical general-purpose protocol for verifiable computation may be significantly closer to reality than previously realized.Second, we describe a set of techniques that achieve genuine scalability for protocols fine-tuned for specific important problems in streaming and database processing. Focusing in particular on noninteractive protocols for problems ranging from matrix-vector multiplication to bipartite perfect matching, we build on prior work [8,15] to achieve a prover that runs in nearly linear-time, while obtaining optimal tradeoffs between communication cost and the user's working memory. Existing techniques required (substantially) superlinear time for the prover. Finally, we develop improved interactive protocols for specific problems based on a linearization technique originally due to Shen [34]. We argue that even if general-purpose methods improve, fine-tuned protocols will remain valuable in real-world settings for key problems, and hence special attention to specific problems is warranted.

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“…We, however, need a stateful version of verifiable RAM computation. Braun et al also informally proposed and implemented verifiable RAM computation [7].…”

Section: Handling Malicious Serversmentioning

confidence: 99%

Verifiable Oblivious Storage

Apon

Katz

Shi

et al. 2014

Lecture Notes in Computer Science

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We formalize the notion of Verifiable Oblivious Storage (VOS), where a client outsources the storage of data to a server while ensuring data confidentiality, access pattern privacy, and integrity and freshness of data accesses. VOS generalizes the notion of Oblivious RAM (ORAM) in that it allows the server to perform computation, and also explicitly considers data integrity and freshness.We show that allowing server-side computation enables us to construct asymptotically more efficient VOS schemes whose bandwidth overhead cannot be matched by any ORAM scheme, due to a known lower bound by Goldreich and Ostrovsky. Specifically, for large block sizes we can construct a VOS scheme with constant bandwidth per query; further, answering queries requires only poly-logarithmic server computation. We describe applications of VOS to Dynamic Proofs of Retrievability, and RAM-model secure multi-party computation.

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Verifying computations with state

Cited by 121 publications

References 72 publications

Incentivized Outsourced Computation Resistant to Malicious Contractors

Incentivized Outsourced Computation Resistant to Malicious Contractors

Practical verified computation with streaming interactive proofs

Verifiable Oblivious Storage

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