Local differential privacy and its applications: A comprehensive survey

M Yang, T Guo, T Zhu, I Tjuawinata, J Zhao… - Computer Standards & …, 2024 - Elsevier
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 …

Privacy-preserved and Responsible Recommenders: From Conventional Defense to Federated Learning and Blockchain

W Ali, X Zhou, J Shao - ACM Computing Surveys, 2024 - dl.acm.org
Recommender systems (RS) play an integral role in many online platforms. Exponential
growth and potential commercial interests are raising significant concerns around privacy …

Fed-DR-Filter: Using global data representation to reduce the impact of noisy labels on the performance of federated learning

S Duan, C Liu, Z Cao, X Jin, P Han - Future Generation Computer Systems, 2022 - Elsevier
The label noise is a serious problem limiting the performance of federated learning.
According to the performance evaluation for the trained federated models, data selection …

Hide me behind the noise: Local differential privacy for indoor location privacy

H Navidan, V Moghtadaiee, N Nazaran… - 2022 IEEE European …, 2022 - ieeexplore.ieee.org
The advent of numerous indoor location-based services (LBSs) and the widespread use of
many types of mobile devices in indoor environments have resulted in generating a massive …

Vehicle-based secure location clustering for IoT-equipped building and facility management in smart city

H Wu, L Li, Y Liu, X Wu - Building and Environment, 2022 - Elsevier
Vehicles equipped with various sensing devices have the strong ability to generate location
information, which is beneficial to a lot of applications in smart city. In special, it is important …

Trust Mechanism Privacy Protection Scheme Combining Blockchain and Multi-Party Evaluation

Z Shen, Y Wang, H Wang, P Liu, K Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Aiming to address issues of query request submission, data transmission leakage, and
vehicle privacy leakage caused by untrustworthy cooperating Partners (CPs) in privacy …

An efficient privacy-preserving point-of-interest recommendation model based on local differential privacy

C Xu, X Mei, D Liu, K Zhao, AS Ding - Complex & Intelligent Systems, 2023 - Springer
With the rapid development of point-of-interest (POI) recommendation services, how to
utilize the multiple types of users' information safely and effectively for a better …

Where Have You Been? A Study of Privacy Risk for Point-of-Interest Recommendation

K Cai, J Zhang, Z Hong, W Shand, G Wang… - Proceedings of the 30th …, 2024 - dl.acm.org
As location-based services (LBS) have grown in popularity, more human mobility data has
been collected. The collected data can be used to build machine learning (ML) models for …

Location Entropy-based privacy protection algorithm for social internet of vehicles

L Xing, Y Huang, J Gao, X Jia, H Wu, H Ma - Wireless Personal …, 2023 - Springer
Abstract In the Social Internet of Vehicles (SIoV), sharing data among entities is prone to
leaking private data. Protecting vehicle users privacy through encryption and anonymous …

Local Differential Privacy for correlated location data release in ITS

KM Chong, A Malip - Computer Networks, 2024 - Elsevier
The ubiquity of location positioning devices has facilitated the implementation of various
Intelligent Transportation System (ITS) applications that generate an enormous volume of …