Exposing and mitigating privacy loss in crowdsourced survey platforms

Exposing and mitigating privacy loss in crowdsourced survey platforms

Crowdsourcing platforms such as Amazon Mechanical Turk and Google Consumer Surveys can profile users based on their inputs to online surveys. In this work we first demonstrate how easily user privacy can be compromised by collating information from multiple surveys. We then propose, develop, and evalu...

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Bibliographic Details
Main Authors: KANDAPPU, Thivya, SIVARAMAN, Vijay, FRIEDMAN, Arik, BORELL, Roksana
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2013
Subjects:
Obfuscation
Privacy
Surveys
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/5390
https://ink.library.smu.edu.sg/context/sis_research/article/6394/viewcontent/Exposing_and_mitigating_privacy_loss_in_crowdsourced_survey_platforms.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:Crowdsourcing platforms such as Amazon Mechanical Turk and Google Consumer Surveys can profile users based on their inputs to online surveys. In this work we first demonstrate how easily user privacy can be compromised by collating information from multiple surveys. We then propose, develop, and evaluate a crowdsourcing survey platform called Loki that allows users to control their privacy loss via atsource obfuscation.

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