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Batch verifiable computation of outsourced functions

机译:批量验证可计算的外包功能

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Verifiable delegation of computation has attracted considerable attention in recent years and had resulted in a number of delegation models. In the verifiable computation model of Gennaro et al., a client wants to delegate the computation of a function to a cloud server. The client generates an encoding of the function that will be stored on the cloud server, and has the property that the cloud server can compute the function on any client's supplied input together with a correctness proof. The proof will allow the client to verify the correctness of the computation by the server using substantially less time than performing the computation itself. In all existing verifiable computation schemes the encoding of the delegated function requires at least twice as much cloud storage as the function itself. This stringent requirement on storage can become a bottleneck in practice. In this paper, we introduce batch verifiable computation which enables the simultaneous delegation of multiple functions. We construct batch verifiable computation schemes that effectively reduce the requirement on cloud storage while preserving efficient client verification. To delegate functions, our batch verifiable computation schemes only require as much cloud storage as the functions themselves. Our schemes are asymptotically optimal in terms of cloud storage in the sense that as . We start with an information-theoretic construction and then introduce computational assumptions to obtain the above efficiencies.
机译:可验证的计算委托近年来引起了相当大的关注,并产生了许多委托模型。在Gennaro等人的可验证计算模型中,客户端希望将功能的计算委托给云服务器。客户端生成将存储在云服务器上的功能的编码,并具有云服务器可以在客户端提供的任何输入上计算功能以及正确性证明的特性。该证明将允许客户端使用比执行计算本身少得多的时间来验证服务器计算的正确性。在所有现有的可验证计算方案中,委托函数的编码至少需要函数本身的两倍的云存储量。在实践中,对存储的这种严格要求可能成为瓶颈。在本文中,我们介绍了可批量验证的计算,它可以同时委派多个功能。我们构建了可批验证的计算方案,可以有效地减少对云存储的需求,同时保留有效的客户端验证。为了委托功能,我们的可批验证计算方案仅需要与功能本身一样多的云存储。就云存储而言,我们的方案是渐近最优的。我们从信息理论的构建开始,然后介绍计算假设以获得上述效率。

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