帮我翻译成英语图7给出了不同算法在执行过程中因用户属性数量变化产生的算法成功率差异。从该图中可以看出隐私信息检索类的算法如可计算PIR、层次PIR、近似PIR和本文算法这些算法的执行成功率都相对较高。这主要是因为这些算法主要通过对自身信息或者属性的加密实现隐私保护的并不需要像泛化方法一样去寻找具有同类属性或者同类特征的泛化用户完成隐私保护。虽然本章所提出的算法需要对用户表现出的各种属性进行加密处理

Figure 7 shows the differences in algorithm success rates caused by changes in the number of user attributes during the execution process. It can be seen from the figure that privacy information retrieval algorithms (such as computable PIR, hierarchical PIR, approximate PIR, and the algorithm proposed in this paper) have relatively high success rates. This is mainly because these algorithms achieve privacy protection by encrypting their own information or attributes, without the need to find generalized users with similar attributes or features like generalization methods. Although the algorithm proposed in this chapter requires encryption of various attributes displayed by users, this processing does not cause significant fluctuations due to changes in the number of attributes. Therefore, like other PIR-based algorithms, the success rate of this algorithm is better than that of generalization algorithms. For the other two generalization algorithms participating in the comparison, both algorithms require finding generalized users with similar attributes to complete privacy protection processing for the applicant user. Therefore, as the number of attributes increases, the degree of reduction in the success rate of the algorithm is higher than that of PIR algorithms. In addition, the main reason for the reduction in the success rate of non-attribute encryption strategy algorithms in the above PIR algorithms with the increase in the number of attributes is similar to the success rate of attacks. The increase in the number of attributes increases the amount of background knowledge available to attackers, and more background knowledge directly allows attackers to guess, associate, and obtain user privacy information, leading to the failure of algorithm privacy protection. Therefore, these PIR algorithms will also experience a decrease in the success rate of algorithm execution due to an increase in the number of attributes