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Privacy Inference Analysis on Event-Based Social Networks

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Social Informatics (SocInfo 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10047))

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Abstract

In this paper, we provide a comprehensive study of privacy threats by bridging user’s online and offline social activities. We adopt the recently emerged Event-Based Social Networks (EBSNs) such as Meetup as an example. Due to the intrinsic interrelated nature of users’ online and offline social activities, our research revealed that using several simple yet effective privacy inference models, user’s privacy of online group membership and offline event attendance can be inferred with high accuracy. The level of privacy threats by bridging user’s online and offline social activities is remarkably severe.

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Notes

  1. 1.

    https://www.meetup.com/about/.

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Author information

Authors and Affiliations

  1. Department of Information Systems, University of Maryland, Baltimore, USA

    Cailing Dong & Bin Zhou

Authors
  1. Cailing Dong
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  2. Bin Zhou
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Corresponding author

Correspondence to Bin Zhou .

Editor information

Editors and Affiliations

  1. University of Washington, Seattle, Washington, USA

    Emma Spiro

  2. Indiana University, Bloomington, Indiana, USA

    Yong-Yeol Ahn

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Dong, C., Zhou, B. (2016). Privacy Inference Analysis on Event-Based Social Networks. In: Spiro, E., Ahn, YY. (eds) Social Informatics. SocInfo 2016. Lecture Notes in Computer Science(), vol 10047. Springer, Cham. https://doi.org/10.1007/978-3-319-47874-6_29

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  • DOI: https://doi.org/10.1007/978-3-319-47874-6_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47873-9

  • Online ISBN: 978-3-319-47874-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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