LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale.

Rogers Ryan,Subramaniam Subbu, Peng Sean,Durfee David, Lee Seunghyun, Kancha Santosh Kumar, Sahay Shraddha,Ahammad Parvez

J. Priv. Confidentiality(2021)

引用 10|浏览26
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摘要
We present a privacy system that leverages differential privacy to protect LinkedIn members' data while also providing audience engagement insights to enable marketing analytics related applications. We detail the differentially private algorithms and other privacy safeguards used to provide results that can be used with existing real-time data analytics platforms, specifically with the open sourced Pinot system. Our privacy system provides user-level privacy guarantees. As part of our privacy system, we include a budget management service that enforces a strict differential privacy budget on the returned results to the analyst. This budget management service brings together the latest research in differential privacy into a product to maintain utility given a fixed differential privacy budget.
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关键词
differential privacy,scale,data analytics,privacy,api
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