most citedDPOAD: Differentially Private Outsourcing of Anomaly Detection through Iterative Sensitivity Learning

2 citations · 2 across the 2 of their papers we have counts for

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cs.CR2022★ 2 cited

DPOAD: Differentially Private Outsourcing of Anomaly Detection through Iterative Sensitivity Learning

Meisam Mohammady, Han Wang, Lingyu Wang +6

Outsourcing anomaly detection to third-parties can allow data owners to overcome resource constraints (e.g., in lightweight IoT devices), facilitate collaborative analysis (e.g., u…

cs.CR2020

RDP: A Universal and Automated Approach to Optimizing the Randomization Mechanisms of Differential Privacy for Utility Metrics with No Known Optimal Distributions

Meisam Mohammady, Shangyu Xie, Yuan Hong +4

Differential privacy (DP) has emerged as a de facto standard privacy notion for a wide range of applications. Since the meaning of data utility in different applications may vastly…