In this work, we investigate theoretical and practical aspects of *zero-knowledge proofs for cluster computations*. We design, build, and evaluate zero-knowledge proof systems for which: (i) a proof attests to the correct execution of a cluster computation; and (ii) generating the proof is itself a cluster computation that is similar in structure and complexity to the original one. Concretely, we focus on MapReduce, an elegant and popular form of cluster computing.
Previous zero-knowledge proof systems can in principle prove a MapReduce computation's correctness, via a monolithic NP statement that reasons about all mappers, all reducers, and shuffling. However, it is not clear how to generate the proof for such monolithic statements via parallel execution by a distributed system. Our work demonstrates, by theory and implementation, that proof generation can be similar in structure and complexity to the original cluster computation.
Our main technique is a bootstrapping theorem for succinct non-interactive arguments of knowledge (SNARKs) that shows how, via recursive proof composition and Proof-Carrying Data, it is possible to transform any SNARK into a *distributed SNARK for MapReduce* which proves, piecewise and in a distributed way, the correctness of every step in the original MapReduce computation as well as their global consistency.
Category / Keywords: cryptographic protocols / zero knowledge, cluster computing, MapReduce, proof-carrying data, succinct arguments Original Publication (with major differences): IACR-EUROCRYPT-2015 Date: received 26 Apr 2015, last revised 28 Apr 2015 Contact author: alexch at berkeley edu Available format(s): PDF | BibTeX Citation Version: 20150428:110109 (All versions of this report) Short URL: ia.cr/2015/377