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

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