Towards a framework for privacy-aware mobile crowdsourcing

Yang Wang, Yun Huang, Claudia Louis

Research output: Chapter in Book/Entry/PoemConference contribution

14 Scopus citations

Abstract

The practice of employing "the crowd" to help solve an organization's problems first became popular in the business sector, and has since spread to public and not-for-profit organizations. Input from the crowd can be solicited using different mechanisms involving various types of web-based applications, or the more recent trend of employing mobile phones with sensing capabilities. However, these crowdsourcing systems may lead to various privacy and security risks which can then hinder the adoption of these services. How to identify and address these potential risks in such systems has both research and practical value. This paper presents two aspects of our work in this emerging space. First, we describe a survey of potential privacy and security risks in mobile crowdsourcing systems (MCSS). Second, we describe our PEALS framework to support privacy-aware mobile crowdsourcing.

Original languageEnglish (US)
Title of host publicationProceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013
Pages454-459
Number of pages6
DOIs
StatePublished - 2013
Event2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013 - Washington, DC, United States
Duration: Sep 8 2013Sep 14 2013

Publication series

NameProceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013

Other

Other2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013
Country/TerritoryUnited States
CityWashington, DC
Period9/8/139/14/13

ASJC Scopus subject areas

  • Software

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