Computer Science > Information Theory
[Submitted on 11 Oct 2025
]
Title: An information theorist's tour of differential privacy
Title: 信息论学者对差分隐私的游览
Abstract: Since being proposed in 2006, differential privacy has become a standard method for quantifying certain risks in publishing or sharing analyses of sensitive data. At its heart, differential privacy measures risk in terms of the differences between probability distributions, which is a central topic in information theory. A differentially private algorithm is a channel between the underlying data and the output of the analysis. Seen in this way, the guarantees made by differential privacy can be understood in terms of properties of this channel. In this article we examine a few of the key connections between information theory and the formulation/application of differential privacy, giving an ``operational significance'' for relevant information measures.
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