函数隐私保护的批量可验证边缘计算方案

Edge computing, a new distributed computing paradigm consists of multiple edge nodes between cloud servers and local users cooperating to perform outsourced storage and computation tasks. Nevertheless, in untrustworthy environments, edge nodes can destroy user data privacy and outsourced functions, disrupt the correct execution of protocols through arbitrary behaviors, and return incorrect computation results. Currently, the correctness verification schemes of edge computation results with data privacy and function privacy protection are mainly realized by bilinear pairing or aggregated signature techniques, which have huge computational and communication overheads and cannot simultaneously meet the batch verifiability requirements of multi-user, multi-input, and multi-function. To solve the above problems, this study proposes a lightweight batch-verifiable edge computing scheme to realize efficient batch private and public verification of computation results returned by edge nodes. Specifically, in the setting of multiple users, multiple inputs, and multiple computational tasks, it splits the shares of both data and evaluated functions by exploiting the finite set theory called uniform (k, n)-set. The proposed scheme makes the verification overhead only linear to both the number and the degree of the evaluated functions, much smaller than the edge computing overhead while protecting input privacy and function privacy.