37 citations · 43 across the 2 of their papers we have counts for
4 papers
DP-Cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications
Sameer Wagh, Xi He, Ashwin Machanavajjhala +1
Differential privacy (DP) has arisen as the state-of-the-art metric for quantifying individual privacy when sensitive data are analyzed, and it is starting to see practical deploym…
Computing Local Sensitivities of Counting Queries with Joins
Yuchao Tao, Xi He, Ashwin Machanavajjhala +1
Local sensitivity of a query Q given a database instance D, i.e. how much the output Q(D) changes when a tuple is added to D or deleted from D, has many applications including quer…
Linear and Range Counting under Metric-based Local Differential Privacy
Zhuolun Xiang, Bolin Ding, Xi He +1
Local differential privacy (LDP) enables private data sharing and analytics without the need for a trusted data collector. Error-optimal primitives (for, e.g., estimating means and…
Crypt: Crypto-Assisted Differential Privacy on Untrusted Servers
Amrita Roy Chowdhury, Chenghong Wang, Xi He +2
Differential privacy (DP) has steadily become the de-facto standard for achieving privacy in data analysis, which is typically implemented either in the "central" or "local" model.…