Determining a discrete set of site-constrained privacy options for users in social networks through stackelberg games

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The privacy policies of an online social network play an important role in determining user involvement and satisfaction, and in turn site profit and success. In this paper, we develop a game theoretic framework to model the relationship between the set of privacy options offered by a social network site and the sharing decisions of its users within these constraints.We model the site and the users in this scenario as the leader and followers, respectively, in a Stackelberg game. We formally establish the conditions under which this game reaches a Nash equilibrium in pure strategies and provide an approximation algorithm for the site to determine a discrete set of privacy options to maximize payoff. We validate hypotheses in our model on data collected from a mock-social network of users’ privacy preferences both within and outside the context of peer influence, and demonstrate that the qualitative assumptions of our model are well-founded.

Original languageEnglish (US)
Title of host publicationDecision and Game Theory for Security - 6th International Conference, GameSec 2015, Proceedings
EditorsM.H.R. Khouzani, Emmanouil Panaousis, George Theodorakopoulos
PublisherSpringer Verlag
Pages208-227
Number of pages20
ISBN (Print)9783319255934
DOIs
StatePublished - 2015
Event6th International Conference on Decision and Game Theory for Security, GameSec 2015 - London, United Kingdom
Duration: Nov 4 2015Nov 5 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9406
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Decision and Game Theory for Security, GameSec 2015
CountryUnited Kingdom
CityLondon
Period11/4/1511/5/15

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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