The Limits of Differential Privacy (and its Misuse in Data Release and Machine Learning)

Understand

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.