PLDP: Personalized Local Differential Privacy for Multidimensional Data Aggregation
The collection of multidimensional crowdsourced data has caused a public concern because of the privacy issues. To address it, local differential privacy (LDP) is proposed to protect the crowdsourced data without much loss of usage, which is popularly used in practice. However, the existing LDP prot...
Main Authors: | Zixuan Shen, Zhihua Xia, Peipeng Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2021-01-01
|
Series: | Security and Communication Networks |
Online Access: | http://dx.doi.org/10.1155/2021/6684179 |
Similar Items
-
Privacy-Preserving Multidimensional Data Aggregation Scheme for Smart Grid
by: Yousheng Zhou, et al.
Published: (2020-01-01) -
Privacy-preserving aggregation of personal health data streams.
by: Jong Wook Kim, et al.
Published: (2018-01-01) -
Privacy-Enhanced and Multifunctional Health Data Aggregation under Differential Privacy Guarantees
by: Hao Ren, et al.
Published: (2016-09-01) -
PAS: An Efficient Privacy-Preserving Multidimensional Aggregation Scheme for Smart Grid
by: Hui Zhu, et al.
Published: (2015-10-01) -
Local Differential Privacy for Evolving Data
by: Matthew Joseph, et al.
Published: (2020-01-01)