Balancing the privacy-utility trade-off: How to draw reliable conclusions from private data

arXiv:2603.12753 · stat.ME, cs.CR · Submitted 2026-03-13 · Read on arXiv

stat.ME, cs.CR

Submitted: 2026-03-13

Updated: 2026-08-28

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Differential Privacy — 25× in this paper · explained in 4 episodes
• Differential Privacy (DP) — 3× in this paper · explained in 7 episodes
• Differentially Private — 3× in this paper · explained in 3 episodes
• AUC — 2× in this paper · explained in 2 episodes
• Actor — 2× in this paper · explained in 3 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Area Under the Curve — 1× in this paper
• Cooperation — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Receiver Operating Characteristic — 1× in this paper
• Trace — 1× in this paper · explained in 2 episodes

Sources

• A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census
• Lomas: A Platform for Confidential Analysis of Private Data
• Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census

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