Local Differential Privacy Protection of High-Dimensional Perceptual Data by the Refined Bayes Network
Although the Crowd-Sensing perception system brings great data value to people through the release and analysis of high-dimensional perception data, it causes great hidden danger to the privacy of participants in the meantime. Currently, various privacy protection methods based on differential priva...
Main Authors: | Chunhua Ju, Qiuyang Gu, Gongxing Wu, Shuangzhu Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/9/2516 |
Similar Items
-
Privacy-Preserving Mobile Crowd Sensing
Published: (2016) -
Bi-Tier Differential Privacy for Precise Auction-Based People-Centric IoT Service
by: Yuan Tian, et al.
Published: (2021-01-01) -
A Perceptual-Based Noise-Agnostic 3D Skeleton Motion Data Refinement Network
by: Shu-Jie Li, et al.
Published: (2020-01-01) -
Security and privacy in perceptual computing
by: Jana, Suman
Published: (2014) -
A Comprehensive Location-Privacy-Awareness Task Selection Mechanism in Mobile Crowd-Sensing
by: Ke Yan, et al.
Published: (2019-01-01)