UPDF AI

Network-Aware Differential Privacy

Zhou Li,Yu Zheng,Tianhao Wang,Sang-Woo Jun

2025 · DOI: 10.48550/arXiv.2509.04710
arXiv.org · 0 Citations

TLDR

This paper identified two focus areas where the network research can offer substantive contributions to the design and deployment of DP, related to network security and topology and hopes to encourage more research that adapt/optimize DP's deployment in various network environments.

Abstract

Differential privacy (DP) is a privacy-enhancement technology (PET) that receives prominent attention from the academia, industry, and government. One main development over the past decade has been the decentralization of DP, including local DP and shuffle DP. Despite that decentralized DP heavily relies on network communications for data collection,we found that: 1) no systematic study has surveyed the research opportunities at the intersection of networking and DP; 2) nor have there been significant efforts to develop DP mechanisms that are explicitly tailored for network environments. In this paper, we seek to address this gap by initiating a new direction of network-aware DP. We identified two focus areas where the network research can offer substantive contributions to the design and deployment of DP, related to network security and topology. Through this work, we hope to encourage more research that adapt/optimize DP's deployment in various network environments.