可验证模指数批计算外包方案

随着云计算的发展,如何将一些耗时的计算任务安全地外包给不受信任的云服务器引起了人们的广泛关注.目前的模指数运算外包方案大多基于两个不可信的服务器,或者外包结果的可验证概率不高.因此,使用随机置换方法,提出了一个新的模指数批计算外包方案.模指数运算的底数和指数对于服务器都是保密的,并且用户的可验证概率接近于1.与已有方案相比,所提方案基于单个不可信服务器实现了输入数据的隐私性,并提高了外包结果的可验证概率.对所提方案进行了模拟实验,测试结果表明外包方案极大地降低了用户的计算代价.

Verifiable outsourcing scheme for batch modular exponentiations

With the development of cloud computing, more and more people focus on how to outsource the expensive computations to the untrusted cloud servers. Currently, the outsourcing schemes for modular exponentiations are mostly based on two untrusted servers, or the checkability is very small. We propose a new outsourcing algorithm for batch modular exponentiations by using the random permutation. The exponent and the base are both private for the server, and the outsourcer can detect the error with probability close to 1. Compared with the previous algorithms, the proposed one is based on a single server, which realizes the privacy of inputs and increases the checkability of the outsourcing result. Finally, we simulate the proposed algorithm, and the experimental result shows that it can greatly reduce the computational cost for the outsourcer.