Better than Composition: How to Answer Multiple Relational Queries under Differential Privacy
Wei Dong, Dajun Sun, Ke Yi
摘要
Answering relational queries under differential privacy has attracted a lot of attention in recent years due to growing concerns on personal privacy, and instance-optimal mechanisms have been developed for a single query. However, most real-world data analytical tasks require multiple queries to be answered under a total privacy budget. The standard solution to extend the single-query mechanism to multiple queries is via privacy composition. However, we observe that this may yield an error bound that could be a √ 𝑑-factor worse from the optimal, where 𝑑 is the number of queries. In this paper, we present a different, more holistic approach that closes this gap. In addition to theoretical optimality, our new mechanism also significantly outperforms privacy composition in practice, especially on more skewed data and large 𝑑. CCS CONCEPTS • Information systems → Database query processing; • Security and privacy → Database and storage security; • Theory of computation → Theory of database privacy and security.
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引用它的顶会 Paper7
- Continual Observation of Joins under Differential PrivacyWei Dong, Zijun Chen, Qiyao Luo, Elaine Shi 等SIGMOD 2024 · 被引用 9 次
- Confidence Intervals for Private Query ProcessingDajun Sun, Wei Dong, Ke YiVLDB 2024 · 被引用 5 次
- Femur: A Flexible Framework for Fast and Secure Querying from Public Key-Value StoreJiaoyi Zhang, Liqiang Peng, Mo Sha, Weiran Liu 等SIGMOD 2025 · 被引用 4 次
- N2E: A General Framework to Reduce Node-Differential Privacy to Edge-Differential Privacy for Graph AnalyticsYihua Hu, Hao Ding, Wei DongSIGMOD 2026 · 被引用 1 次
- A General Framework for Per-record Differential PrivacyXinghe Chen, Dajun Sun, Quanqing Xu, Wei DongSIGMOD 2026
它引用的顶会 Paper6
- Deep Learning with Differential PrivacyMartín Abadi, Andy Chu, Ian J. Goodfellow, H. Brendan McMahan 等CCS 2016 · 被引用 7,620 次
- CoinPress: Practical Private Mean and Covariance EstimationSourav Biswas, Yihe Dong, Gautam Kamath, Jonathan R. UllmanNeurIPS 2020 · 被引用 134 次
- Instance-optimal Mean Estimation Under Differential PrivacyZiyue Huang, Yuting Liang, Ke YiNeurIPS 2021 · 被引用 74 次
- R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign KeysWei Dong, Juanru Fang, Ke Yi, Yuchao Tao 等SIGMOD 2022 · 被引用 41 次
- Computing Local Sensitivities of Counting Queries with JoinsYuchao Tao, Xi He, Ashwin Machanavajjhala, Sudeepa RoySIGMOD 2020 · 被引用 37 次
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