This tutorial studies relationships between differential privacy and various information-theoretic measures by using several selective articles. In particular, we present how these connections can provide new interpretations for the privacy guarantee in systems that deploy differential privacy in an information-theoretic framework. To this end, the tutorial provides an extensive summary on the existing literature that makes use of information-theoretic measures and tools such as mutual information, min-entropy, Kullback-Leibler divergence and rate-distortion function for quantification and characterization of differential privacy in various settings.

翻译：本教程通过使用一些详谨的文章来研究差分隐私和各种信息论测度之间的关系。特别地,我们介绍了这些联系如何为使用信息论框架中的差分隐私的系统提供隐私保障的新解释。为此，本教程提供了一份详尽的文献综述，其中使用信息论测度和工具，如互信息、最小熵、Kullback-Leibler散度和率失真函数来定量和表征不同环境下的差分隐私。