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 …
Federated learning with differential privacy: Algorithms and performance analysis
Federated learning (FL), as a type of distributed machine learning, is capable of significantly
preserving clients' private data from being exposed to adversaries. Nevertheless, private …
preserving clients' private data from being exposed to adversaries. Nevertheless, private …
User-level privacy-preserving federated learning: Analysis and performance optimization
Federated learning (FL), as a type of collaborative machine learning framework, is capable
of preserving private data from mobile terminals (MTs) while training the data into useful …
of preserving private data from mobile terminals (MTs) while training the data into useful …
A survey of differential privacy-based techniques and their applicability to location-based services
The widespread use of mobile devices such as smartphones, tablets, and smartwatches has
led users to constantly generate various location data during their daily activities …
led users to constantly generate various location data during their daily activities …
PFLF: Privacy-preserving federated learning framework for edge computing
H Zhou, G Yang, H Dai, G Liu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Federated learning (FL) can protect clients' privacy from leakage in distributed machine
learning. Applying federated learning to edge computing can protect the privacy of edge …
learning. Applying federated learning to edge computing can protect the privacy of edge …
Low-latency federated learning over wireless channels with differential privacy
In federated learning (FL), model training is distributed over clients and local models are
aggregated by a central server. The performance of uploaded models in such situations can …
aggregated by a central server. The performance of uploaded models in such situations 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 …
Privacy-preserving data aggregation against malicious data mining attack for IoT-enabled smart grid
Internet of Things (IoT)-enabled smart grids can achieve more reliable and high-frequency
data collection and transmission compared with existing grids. However, this frequent data …
data collection and transmission compared with existing grids. However, this frequent data …
Privacy preserving classification on local differential privacy in data centers
With the rise of cloud service providers and the continuous virtualization of data centers,
data center networks are also developing rapidly. As data centers become more and more …
data center networks are also developing rapidly. As data centers become more and more …