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A Visual Model for Privacy Awareness and Understanding in Online Social Networks

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Future Data and Security Engineering (FDSE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11814))

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Abstract

The number of users participating in online social networks is increasing significantly recently. As a result, the amount of information created and shared by them is exploding. On one hand, sharing information online helps people stay in touch with each other, although virtually. But on the other hand, sharing too much information may lead to sensitive personal data being leaked unexpectedly. To protect their users’ private information, online social network providers often employ technical methods like access control and cryptography among others. Although these approaches are good enough for their designated purposes, they provide little to no protection when are used wrongly. To reduce the number of mistakes users may make, online social network providers also offers them visual interfaces, instead of lengthy and boring texts, for privacy settings selection and configuration. Unfortunately, private information is stilled shared publicly, with or without its owners’ awareness. In this paper, we attempt to mitigate the privacy leakage problem by proposing a novel visual model for measuring and representing users’ privacy in online social network environment and associated privacy controller for protecting it. A concrete instance of the model has been designed and implemented. A demonstration of the model instance has been executed for one of the biggest social networks, Facebook. Initial results indicate the effectiveness of the proposed model and its concrete instance. However, a more important and difficult problem is whether online social network providers are willing to apply these results, which may affect sharing activities and go against their business objectives.

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Notes

  1. 1.

    Hootsuite: The global state of digital in 2019 report, https://hootsuite.com/pages/digital-in-2019.

  2. 2.

    Facebook Help Center, https://www.facebook.com/help/227499947267037.

  3. 3.

    Facebook Login for developers, https://developers.facebook.com/docs/facebook-login.

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Acknowledgment

This research is funded by Vietnam National University HoChiMinh City (VNU-HCM) under grant number C2018-20-12. We would like to thank D-STAR lab members from HCMUT who proofread and provided constructive feedback. We also would like to thank volunteer students from my teaching classes who devoted their time and effort in the experiment of this research.

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Authors and Affiliations

  1. Ho Chi Minh City University of Technology, VNU-HCM, Ho Chi Minh City, Vietnam

    Tran Tri Dang

  2. University of Linz, Linz, Austria

    Josef Küng

Authors
  1. Tran Tri Dang
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  2. Josef Küng
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Correspondence to Tran Tri Dang .

Editor information

Editors and Affiliations

  1. Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler Universität Linz, Linz, Austria

    Josef Küng

  3. Hosei University, Tokyo, Japan

    Makoto Takizawa

  4. Telecommunications University, Nha Trang City, Vietnam

    Son Ha Bui

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Dang, T.T., Küng, J. (2019). A Visual Model for Privacy Awareness and Understanding in Online Social Networks. In: Dang, T., Küng, J., Takizawa, M., Bui, S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science(), vol 11814. Springer, Cham. https://doi.org/10.1007/978-3-030-35653-8_26

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  • DOI: https://doi.org/10.1007/978-3-030-35653-8_26

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  • Online ISBN: 978-3-030-35653-8

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