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

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 combined with 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 article, we propose two mechanisms for solving this problem with both efficiency and strong utility guarantees. The first mechanism, called R2T, is simple and efficient, while achieving down-neighborhood optimality with a logarithmic optimality ratio. Down-neighborhood optimality is a new notion of optimality that we introduce for measuring the utilities of DP mechanisms, which can be considered as a natural relaxation of instance optimality, and it is especially suitable for functions with a large or unbounded sensitivity. Our second mechanism further reduces the optimality ratio to a double logarithm, which is also known to be optimal, thus we call this mechanism OPT2. While OPT2 also runs in polynomial time, it does have a higher computational cost than R2T in practice. Both R2T and OPT2 are simple enough that they can be easily implemented on top of any RDBMS and an LP solver. Experimental results show that they offer order-of-magnitude improvements in terms of utility over existing techniques, even those specifically designed for graph pattern counting.

Duke Scholars

Author Ashwinkumar Venkatanaga Machanavajjhala Computer Science