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R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys

Publication ,  Conference
Dong, W; Fang, J; Yi, K; Tao, Y; MacHanavajjhala, A
Published in: Proceedings of the ACM SIGMOD International Conference on Management of Data
June 10, 2022

Answering SPJA queries under differential privacy (DP), including graph pattern counting under node-DP as an important special case, has received considerable attention in recent years. The dual challenge of foreign-key constraints and self-joins is particularly tricky to deal with, and no existing DP mechanisms can correctly handle both. For the special case of graph pattern counting under node-DP, the existing mechanisms are correct (i.e., satisfy DP), but they do not offer nontrivial utility guarantees or are very complicated and costly. In this paper, we propose the first DP mechanism for answering arbitrary SPJA queries in a database with foreign-key constraints. Meanwhile, it achieves a fairly strong notion of optimality, which can be considered as a small and natural relaxation of instance optimality. Finally, our mechanism is simple enough that it can be easily implemented on top of any RDBMS and an LP solver. Experimental results show that it offers order-of-magnitude improvements in terms of utility over existing techniques, even those specifically designed for graph pattern counting.

Duke Scholars

Published In

Proceedings of the ACM SIGMOD International Conference on Management of Data

DOI

ISSN

0730-8078

ISBN

9781450392495

Publication Date

June 10, 2022

Start / End Page

759 / 772
 

Citation

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Dong, W., Fang, J., Yi, K., Tao, Y., & MacHanavajjhala, A. (2022). R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys. In Proceedings of the ACM SIGMOD International Conference on Management of Data (pp. 759–772). https://doi.org/10.1145/3514221.3517844
Dong, W., J. Fang, K. Yi, Y. Tao, and A. MacHanavajjhala. “R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys.” In Proceedings of the ACM SIGMOD International Conference on Management of Data, 759–72, 2022. https://doi.org/10.1145/3514221.3517844.
Dong W, Fang J, Yi K, Tao Y, MacHanavajjhala A. R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. 2022. p. 759–72.
Dong, W., et al. “R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys.” Proceedings of the ACM SIGMOD International Conference on Management of Data, 2022, pp. 759–72. Scopus, doi:10.1145/3514221.3517844.
Dong W, Fang J, Yi K, Tao Y, MacHanavajjhala A. R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys. Proceedings of the ACM SIGMOD International Conference on Management of Data. 2022. p. 759–772.

Published In

Proceedings of the ACM SIGMOD International Conference on Management of Data

DOI

ISSN

0730-8078

ISBN

9781450392495

Publication Date

June 10, 2022

Start / End Page

759 / 772