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cc 14(1): e4

Research Article

A Game Theoretic Approach for Modeling Privacy Settings of an Online Social Network

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  • @ARTICLE{10.4108/cc.1.1.e4,
        author={Jundong Chen and Ankunda  R. Kiremire and Matthias R.  Brust and Vir V. Phoha},
        title={A Game Theoretic Approach for Modeling Privacy Settings of an Online Social Network},
        journal={EAI Endorsed Transactions on Collaborative Computing},
        volume={1},
        number={1},
        publisher={ICST},
        journal_a={CC},
        year={2014},
        month={5},
        keywords={game theory, social network, privacy settings, network topology},
        doi={10.4108/cc.1.1.e4}
    }
    
  • Jundong Chen
    Ankunda R. Kiremire
    Matthias R. Brust
    Vir V. Phoha
    Year: 2014
    A Game Theoretic Approach for Modeling Privacy Settings of an Online Social Network
    CC
    ICST
    DOI: 10.4108/cc.1.1.e4
Jundong Chen1,*, Ankunda R. Kiremire1, Matthias R. Brust1, Vir V. Phoha1
  • 1: Center for Secure Cyberspace, Louisiana Tech University, Ruston, LA 71270, USA
*Contact email: jdc074@latech.edu

Abstract

Users of online social networks often adjust their privacy settings to control how much information on their profiles is accessible to other users of the networks. While a variety of factors have been shown to affect the privacy strategies of these users, very little work has been done in analyzing how these factors influence each other and collectively contribute towards the users’ privacy strategies. In this paper, we analyze the influence of attribute importance, benefit, risk and network topology on the users’ attribute disclosure behavior by introducing a weighted evolutionary game model. Results show that: irrespective of risk, users aremore likely to reveal theirmost important attributes than their least important attributes; when the users’ range of influence is increased, the risk factor plays a smaller role in attribute disclosure; the network topology exhibits a considerable effect on the privacy in an environment with risk.

Keywords
game theory, social network, privacy settings, network topology
Received
2014-02-14
Accepted
2014-05-23
Published
2014-05-27
Publisher
ICST
http://dx.doi.org/10.4108/cc.1.1.e4

Copyright © 2014 J. Chen, et al., licensed to ICST. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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