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Personalization of Privacy in Mobile Social Networks

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 241))

Abstract

Mobile social networks are characterized by the sharing of user context information, such as the location of one’s mobile device. The location information on a social network enables its operator to offer resources for socialization, such as suggestions of new friends, products, and services, in relation to the user’s geographical area. While some users view such suggestions as a personal gain, others view them as an invasion of privacy. Since this location information is shared by the users on social networks, it can be accessed by the users’ friends and service providers, but also by malicious users. Unauthorized access can pose several risks regarding privacy and security. On the other hand, sharing a user’s location with a particular friend or group of friends while concealing this information from the service provider would guarantee the security and privacy of the user’s information. This paper presents a mobile social networking model with privacy guarantees concerning the sharing of its members’ locations. The model allows users to personalize their privacy by setting rules that determine to whom, when, and where their location information can be made available. The model provides three levels of privacy, personalized by the user, using techniques of anonymity and dissemination or setting the location to ensure the concealment of information before it is made available on the social network. A proof of concept for the proposed model, called RSMPrivacy, was developed for the Android platform. The performance tests showed that the delays generated by the use of RSMPrivacy were proportional to, and justifiable for, the privacy levels desired and chosen by the users. RSMPrivacy was evaluated by 50 users on the aspects of usability and evidence of the efficiency of the techniques in the proposed model.

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Notes

  1. 1.

    https://www.facebook.com/.

  2. 2.

    https://twitter.com/.

  3. 3.

    https://instagram.com/.

  4. 4.

    https://foursquare.com/.

  5. 5.

    https://www.whatsapp.com.

References

  1. Wasserman, S., Faust, K.: Structural Analysis in the Social Sciences. Cambridge University Press, Cambridge (1994)

    Google Scholar 

  2. Toch, E., et al.: Empirical models of privacy in location sharing. In: 12th ACM International Conference on Ubiquitous Computing, pp. 129–138 (2010)

    Google Scholar 

  3. Benisch, M., et al.: Capturing location-privacy preferences: quantifying accuracy and user-burden tradeoffs. In: Personal and Ubiquitous Computing, pp. 679–94 (2011)

    Google Scholar 

  4. Ardagna, C.A., et al.: Privacy-enhanced location services information. In: Digital Privacy: Theory, Technologies and Practices, pp. 307–326. Auerbach Publications (Taylor and Francis Group) (2007)

    Google Scholar 

  5. Anthony, D., Henderson, T., Kotz, D.: Privacy in location aware computing environments. IEEE Pervasive Comput. 6(4), 64–72 (2007)

    Article  Google Scholar 

  6. Gao, H. et al.: Security issues in online social networks. In: IEEE Internet Computing, pp. 56–63 (2011)

    Google Scholar 

  7. Smart, S.W.: TextBook on Spherical Astronomy, 6th edn., 415, p. Cambridge University Press, England (1977)

    Google Scholar 

  8. Williams, Ed.: Aviation Formulary 1.44. http://williams.best.vwh.net/avform.htm#LL. Accessed November 2013

  9. Ribeiro, F.N., Zorzo, S.D.: LPBS – location privacy based system. In: IEEE Symposium on Computers and Communications, pp. 374–379 (2009)

    Google Scholar 

  10. Android. http://www.android.com. Accessed November 2013

  11. Smith, I., Consolvo, S., LaMarca, A., Hightower, J., Scott, J., Sohn, T., Hughes, J., Iachello, G., Abowd, G.D.: Social disclosure of place: from location technology to communication practices. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 134–151. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  12. Toch, E., Cranshaw, J., Hankes-Drielsma, P., Springfield, J., Gage, P., Cranor, L., Hong, J., Sadeh, N.: Locaccino: a privacy-centric location sharing application. In: 12th ACM International Conference Adjunct Papers on Ubiquitous Computing, pp. 381–382 (2010)

    Google Scholar 

  13. Bilogrevic, I., Huguenin, K., Agir, B., Jadliwala, M., Hubaux, J.P.: Adaptive information-sharing for privacy-aware mobile social networks. In: 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 657–666 (2013)

    Google Scholar 

  14. Leon, P., et al.: Why Johnny can’t opt out: a usability evaluation of tools to limit online behavioral advertising. In: SIGCHI Conference on Human Factors in Computing Systems, New York, NY, USA, pp. 589–598 (2012)

    Google Scholar 

  15. Google Maps. https://www.google.com.br/maps. Accessed March 2015

  16. Facebook. https://www.facebook.com. Accessed March 2014

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Correspondence to Tiago Antonio Rosa .

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© 2015 Springer International Publishing Switzerland

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Rosa, T.A., Zorzo, S.D. (2015). Personalization of Privacy in Mobile Social Networks. In: Hammoudi, S., Maciaszek, L., Teniente, E., Camp, O., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2015. Lecture Notes in Business Information Processing, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-29133-8_27

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  • DOI: https://doi.org/10.1007/978-3-319-29133-8_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29132-1

  • Online ISBN: 978-3-319-29133-8

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