Publication Type
Book Chapter
Version
publishedVersion
Publication Date
10-2015
Abstract
Emerging platforms, such as Amazon Mechanical Turk and Google Consumer Surveys, are increasingly being used by researchers and market analysts to crowdsource large-scale survey data from online populations at extremely low cost. However, by participating in successive surveys, workers risk being profiled and targeted, both by surveyors and by the platform itself. In this chapter we provide an overview of privacy in crowdsourcing platforms. We consider the state-of-the-art crowdsourcing platforms and the risks to worker privacy in such platforms, we survey the existing solutions, and later describe and evaluate the design of a privacy conscious crowdsourcing platform prototype, called Loki. We believe that many challenges in the area of privacy in crowdsourced platforms remain, and that this will be an active and important research area for many years to come.
Keywords
Privacy Cost, Privacy Risk, Differential Privacy, Privacy Level, Randomize Response Technique
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Privacy in a digital, networked world
Editor
Sherali Zeadally and Mohamad Badra
First Page
57
Last Page
84
ISBN
9783319084695
Identifier
https://doi-org.libproxy.smu.edu.sg/10.1007/978-3-319-08470-1_4
Publisher
Springer
City or Country
Switzerland
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.