Local differential privacy and its applications: A comprehensive survey
With the rapid development of low-cost consumer electronics and pervasive adoption of next
generation wireless communication technologies, a tremendous amount of data has been …
generation wireless communication technologies, a tremendous amount of data has been …
A comprehensive survey on local differential privacy toward data statistics and analysis
T Wang, X Zhang, J Feng, X Yang - Sensors, 2020 - mdpi.com
Collecting and analyzing massive data generated from smart devices have become
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …
Hiding among the clones: A simple and nearly optimal analysis of privacy amplification by shuffling
Recent work of Erlingsson, Feldman, Mironov, Raghunathan, Talwar, and Thakurta 1
demonstrates that random shuffling amplifies differential privacy guarantees of locally …
demonstrates that random shuffling amplifies differential privacy guarantees of locally …
Differentially private data publishing and analysis: A survey
Differential privacy is an essential and prevalent privacy model that has been widely
explored in recent decades. This survey provides a comprehensive and structured overview …
explored in recent decades. This survey provides a comprehensive and structured overview …
Applications of differential privacy in social network analysis: A survey
Differential privacy provides strong privacy preservation guarantee in information sharing.
As social network analysis has been enjoying many applications, it opens a new arena for …
As social network analysis has been enjoying many applications, it opens a new arena for …
Hadamard response: Estimating distributions privately, efficiently, and with little communication
We study the problem of estimating $ k $-ary distributions under $\eps $-local differential
privacy. $ n $ samples are distributed across users who send privatized versions of their …
privacy. $ n $ samples are distributed across users who send privatized versions of their …
Optimal schemes for discrete distribution estimation under locally differential privacy
We consider the minimax estimation problem of a discrete distribution with support size k
under privacy constraints. A privatization scheme is applied to each raw sample …
under privacy constraints. A privatization scheme is applied to each raw sample …
Locally private graph neural networks
S Sajadmanesh, D Gatica-Perez - … of the 2021 ACM SIGSAC conference …, 2021 - dl.acm.org
Graph Neural Networks (GNNs) have demonstrated superior performance in learning node
representations for various graph inference tasks. However, learning over graph data can …
representations for various graph inference tasks. However, learning over graph data can …
A comprehensive survey on local differential privacy
X Xiong, S Liu, D Li, Z Cai, X Niu - Security and Communication …, 2020 - Wiley Online Library
With the advent of the era of big data, privacy issues have been becoming a hot topic in
public. Local differential privacy (LDP) is a state‐of‐the‐art privacy preservation technique …
public. Local differential privacy (LDP) is a state‐of‐the‐art privacy preservation technique …
L-srr: Local differential privacy for location-based services with staircase randomized response
Location-based services (LBS) have been significantly developed and widely deployed in
mobile devices. It is also well-known that LBS applications may result in severe privacy …
mobile devices. It is also well-known that LBS applications may result in severe privacy …