Title
IronM: Privacy-Preserving Reliability Estimation of Heterogeneous Data for Mobile Crowdsensing
Abstract
A reliable mobile crowdsensing (MCS) application usually relies on sufficient participants and trustworthy data. However, privacy concerns reduce participants' willingness to participate in sensing tasks. The uncertainty of participant behavior and heterogeneity of sensing devices result in the unreliability of sensing data and further bring unreliable MCS services. Hence, it is crucial to estimat...
Year
DOI
Venue
2020
10.1109/JIOT.2020.2975546
IEEE Internet of Things Journal
Keywords
DocType
Volume
Reliability,Sensors,Data privacy,Estimation,Task analysis,Internet of Things,Privacy
Journal
7
Issue
ISSN
Citations 
6
2327-4662
2
PageRank 
References 
Authors
0.36
0
5
Name
Order
Citations
PageRank
Bowen Zhao1146.32
Shaohua Tang248148.22
Ximeng Liu313531.84
Xinglin Zhang4417.02
Wei-Neng Chen514313.16