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.
REF examine crowd-sourced survey platforms and show how easily user privacy can be compromised by collating information from multiple surveys.
Exposing and mitigating privacy loss in crowdsourced survey platforms
CoNEXT Student Workhop '13
Computer Science Engineering