We study fine-grained error bounds for differentially private algorithms for counting under continual observation. Our main insight is that the matrix mechanism when using lower …
We study the problem of maintaining a differentially private decaying sum under continual observation. We give a unifying framework and an efficient algorithm for this problem for any …
JD Andersson, R Pagh - Advances in Neural Information …, 2024 - proceedings.neurips.cc
In privacy under continual observation we study how to release differentially private estimates based on a dataset that evolves over time. The problem of releasing private prefix …
W Dong, Q Luo, K Yi - 2023 IEEE Symposium on Security and …, 2023 - ieeexplore.ieee.org
In the foundational work of Dwork et al.[15] on continual observation under differential privacy (DP), two privacy models have been proposed: event-level DP and user-level DP …
In the task of differentially private (DP) continual counting, we receive a stream of increments and our goal is to output an approximate running total of these increments, without revealing …
The hereditary discrepancy of a set system is a certain quantitative measure of the pseudorandom properties of the system. Roughly, hereditary discrepancy measures how …
We introduce the concurrent shuffle model of differential privacy. In this model we have multiple concurrent shufflers permuting messages from different, possibly overlapping …
We study the problem of performing counting queries at different levels in hierarchical structures while preserving individuals' privacy. Motivated by applications, we propose a …
W Dong, Z Chen, Q Luo, E Shi, K Yi - … of the ACM on Management of …, 2024 - dl.acm.org
The problem of continual observation under differential privacy has been studied extensively in the literature. However, all existing works, with the exception of [28, 51], have only studied …