基于加性秘密共享的洗牌协议的设计

Design of shuffling protocol based on additive secret sharing

针对现有基于秘密共享的洗牌协议缺少流程实现的具体算法、解决方案多采用公钥、处理大规模数据集时效率低、适用性不足等问题,提出了一种单边洗牌协议,并在此基础上设计了一种基于加性秘密共享的洗牌协议。通过不经意传输协议构建份额转换算法,在不暴露原数据集的前提下完成了洗牌;利用Benes排列网络实现洗牌分解,将复杂的洗牌任务分解为多个子任务,提高了大规模数据集的处理效率;最终通过加性秘密共享,确保将洗牌份额安全地分配给参与方。对所提协议的正确性进行了严格分析,并运用理想-现实模拟范式对其安全性进行了评估。与现有文献相比,所提协议在安全性上能够达到当前安全标准,并在处理大规模数据集时有较高的效率。此外,所提协议的适用性得到了提升,进一步促进了其在当下环境中的应用。

Aiming at the problems such as lack of specific algorithms for process implementation,using public keys in most of the solutions,low efficiency in dealing with large-scale data sets,and lack of applicability,a unilateral shuffling protocol was proposed,and on this basis,a shuffling protocol based on additive secret sharing was designed.The share conversion algorithm was constructed through the casual transfer protocol,and the shuffling was completed without exposing the original data set.The shuffling task was decomposed into multiple sub-tasks by the Benes arrangement network,which improved the efficiency of large-scale data sets.Finally,through the additive secret sharing,the shuffling shares were safely distributed to the participants.The correctness of the proposed shuffling protocol was analyzed strictly,and its security property was evaluated by using an ideal-reality simulation paradigm.Compared with the existing literature,the proposed protocol can meet the current security standards in security,and has high efficiency in processing large-scale data sets.It improves the applicability of the protocol and further promotes its application in the current environment.