A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries
This addresses a key limitation in privacy-preserving data analysis for database queries, offering improved theoretical guarantees.
The paper tackles the problem of releasing result sizes of conjunctive queries under differential privacy without optimality guarantees, and provides the first mechanism with a strong near-instance-optimality guarantee.
Releasing the result size of conjunctive queries and graph pattern queries under differential privacy (DP) has received considerable attention in the literature, but existing solutions do not offer any optimality guarantees. We provide the first DP mechanism for this problem with a fairly strong notion of optimality, which can be considered as a natural relaxation of instance-optimality to a constant.