In outsourced classification services, classifier owners outsource their classifiers to remote servers due to resource constraints, and users can request classification services from this server. What attracts us is that the users’ query data, classification results, and classifier privacy are all well protected during classification. However, we introduce a threat model that makes it easy for adversaries to attack. Thus, to ensure its security, this model should be modified. In addition, considering the low efficiency of Paillier cryptosystem, the classification phase is accompanied by problems of low computational efficiency and large occupied bandwidth consumption. In this paper, we use a substitutive OU cryptosystem, which effectively saves computational and communication costs. Moreover, experimental results show that the improvement enhances the efficiency of the scheme and reduces the bandwidth consumption.

在外包分类服务中，由于资源限制，分类器所有者将其分类器外包给远程服务器，并且用户可以从该服务器请求分类服务。吸引我们的是，用户的查询数据，分类结果和分类器隐私在分类期间都得到了很好的保护。但是，我们引入了一种威胁模型，使攻击者易于攻击。因此，为了确保其安全性，应修改此模型。另外，考虑到Paillier密码系统的低效率，分类阶段伴随着计算效率低和占用带宽消耗大的问题。在本文中，我们使用替代OU密码系统，可有效节省计算和通信成本。此外，