论文标题
差异隐私的限制（及其在数据发布和机器学习中的滥用）
The Limits of Differential Privacy (and its Misuse in Data Release and Machine Learning)
论文作者
论文摘要
差异隐私（DP）是一个整洁的隐私定义，可以与交互式查询的某些明确定义的数据使用并存。但是，DP既不是所有隐私问题的银弹，也不是所有以前的隐私模型的替代品。实际上，试图将其使用范围扩展到其设计的设置之外时，应谨慎行事。本文回顾了DP的局限性及其对单个数据收集，单个数据发布和机器学习的滥用。
Differential privacy (DP) is a neat privacy definition that can co-exist with certain well-defined data uses in the context of interactive queries. However, DP is neither a silver bullet for all privacy problems nor a replacement for all previous privacy models. In fact, extreme care should be exercised when trying to extend its use beyond the setting it was designed for. This paper reviews the limitations of DP and its misuse for individual data collection, individual data release, and machine learning.
