A Survey of Participant Privacy in Spatial Crowdsourcing

PhD Qualifying Examination


Title: "A Survey of Participant Privacy in Spatial Crowdsourcing"

by

Mr. Mingzhe LI


Abstract:

With the popularity of sensor-rich mobile devices (e.g. smart phones and 
wearable devices), spatial crowdsourcing has emerged as an effective method for 
data collection and processing, and has enabled a broad range of novel 
applications. Spatial crowdsourcing consists of location-related tasks which 
require participants to perform them by traveling to the specific locations. 
While spatial crowdsourcing has demonstrated advantages in mobility, 
scalability, time-efficiency, and human intelligence, it requires to collect 
detailed information from sensors and participants. Collecting such information 
may infringe the privacy of participants in various aspects through 
identification or disclosure of sensitive characteristics, which increases the 
system vulnerability and, in turn, reduces participa- tion. As a result, recent 
years have witnessed the relentless research efforts for protecting 
participants’ privacy in spatial crowdsourcing.

In this survey, we analyze different attributes of spatial crowdsourcing and 
assess the threats to participant privacy when personal information is 
divulged. Specifically, we provide a systematical review about various task 
assignment approaches and outline how privacy preserving mechanisms are 
leveraged to protect location privacy for partic- ipants in existing spatial 
crowdsourcing applications. Finally, we sketch out continuing challenges facing 
participant privacy-preserving mechanisms during task assignment in spatial 
crowdsourcing.


Date:			Thursday, 22 November 2018

Time:                  	5:00pm - 7:00pm

Venue:                  Room 3494
                         Lifts 25/26

Committee Members:	Prof. Wei Wang (Supervisor)
 			Prof. Jin Zhang (Supervisor, SUSTC)
 			Prof. Lei Chen (Chairperson)
 			Prof. Kai Chen
 			Prof. Bo Li


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