User Vulnerability and Its Reduction on a Social Networking Site

Privacy and security are major concerns for many users of social media. When users share information (e.g., data and photos) with friends, they can make their friends vulnerable to security and privacy breaches with dire consequences. With the continuous expansion of a user’s social network, privacy settings alone are often inadequate to protect a user’s profile. In this research, we aim to address some critical issues related to privacy protection: (1) How can we measure and assess individual users’ vulnerability? (2) With the diversity of one’s social network friends, how can one figure out an effective approach to maintaining balance between vulnerability and social utility? In this work, first we present a novel way to define vulnerable friends from an individual user’s perspective. User vulnerability is dependent on whether or not the user’s friends’ privacy settings protect the friend and the individual’s network of friends (which includes the user). We show that it is feasible to measure and assess user vulnerability and reduce one’s vulnerability without changing the structure of a social networking site. The approach is to unfriend one’s most vulnerable friends. However, when such a vulnerable friend is also socially important, unfriending him or her would significantly reduce one’s own social status. We formulate this novel problem as vulnerability minimization with social utility constraints. We formally define the optimization problem and provide an approximation algorithm with a proven bound. Finally, we conduct a large-scale evaluation of a new framework using a Facebook dataset. We resort to experiments and observe how much vulnerability an individual user can be decreased by unfriending a vulnerable friend. We compare performance of different unfriending strategies and discuss the security risk of new friend requests. Additionally, by employing different forms of social utility, we confirm that the balance between user vulnerability and social utility can be practically achieved.

[1]  Eric Gilbert,et al.  Predicting tie strength with social media , 2009, CHI.

[2]  Balaji Rajagopalan,et al.  Knowledge-sharing and influence in online social networks via viral marketing , 2003, CACM.

[3]  Carlo Caduff International Encyclopedia of the Social Sciences , 2007 .

[4]  Reza Zafarani,et al.  Social Media Mining: An Introduction , 2014 .

[5]  Anna Cinzia Squicciarini,et al.  WWW 2009 MADRID! Track: Security and Privacy / Session: Web Privacy Collective Privacy Management in Social Networks , 2022 .

[6]  M. L. Fisher,et al.  An analysis of approximations for maximizing submodular set functions—I , 1978, Math. Program..

[7]  P. Baran The Theory of the Leisure Class , 1957 .

[8]  LiuHuan,et al.  User Vulnerability and Its Reduction on a Social Networking Site , 2014 .

[9]  G. Becker A Theory of Social Interactions , 1974 .

[10]  Huan Liu,et al.  Community evolution in dynamic multi-mode networks , 2008, KDD.

[11]  Huan Liu,et al.  Mining Social Media: A Brief Introduction , 2012 .

[12]  Huan Liu,et al.  A tool for collecting provenance data in social media , 2013, KDD.

[13]  Philip S. Yu,et al.  Identifying the influential bloggers in a community , 2008, WSDM '08.

[14]  Steven Walczak,et al.  Unfriending on Facebook: Friend Request and Online/Offline Behavior Analysis , 2011, 2011 44th Hawaii International Conference on System Sciences.

[15]  Christos Faloutsos,et al.  On the Vulnerability of Large Graphs , 2010, 2010 IEEE International Conference on Data Mining.

[16]  Vijay V. Vazirani,et al.  Approximation Algorithms , 2001, Springer Berlin Heidelberg.

[17]  Alessandro Acquisti,et al.  Information revelation and privacy in online social networks , 2005, WPES '05.

[18]  Reza Zafarani,et al.  Connecting Corresponding Identities across Communities , 2009, ICWSM.

[19]  Gary Vaynerchuk Crush It!: Why NOW Is the Time to Cash In on Your Passion , 2009 .

[20]  Jon M. Kleinberg,et al.  Group formation in large social networks: membership, growth, and evolution , 2006, KDD '06.

[21]  Chris Arney,et al.  Networks, Crowds, and Markets: Reasoning about a Highly Connected World (Easley, D. and Kleinberg, J.; 2010) [Book Review] , 2013, IEEE Technology and Society Magazine.

[22]  David Stuart Social Media Metrics , 2009 .

[23]  Dennis M. Murphy The Net Delusion: The Dark Side of Internet Freedom , 2012 .

[24]  Michalis Faloutsos,et al.  Gelling, and melting, large graphs by edge manipulation , 2012, CIKM.

[25]  Xiaowei Ying,et al.  Randomizing Social Networks: a Spectrum Preserving Approach , 2008, SDM.

[26]  Rebecca Goolsby,et al.  Social media as crisis platform: The future of community maps/crisis maps , 2010, TIST.

[27]  Maxim Sviridenko,et al.  A note on maximizing a submodular set function subject to a knapsack constraint , 2004, Oper. Res. Lett..

[28]  Evgeny V. Morozov,et al.  Response to Philip N. Howard's review of The Net Delusion: The Dark Side of Internet Freedom , 2011, Perspectives on Politics.

[29]  Daniele Quercia,et al.  Our Twitter Profiles, Our Selves: Predicting Personality with Twitter , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[30]  Bernd Marcus,et al.  Personality in cyberspace: personal Web sites as media for personality expressions and impressions. , 2006, Journal of personality and social psychology.

[31]  Huan Liu,et al.  Mining social media with social theories: a survey , 2014, SKDD.

[32]  Lise Getoor,et al.  To join or not to join: the illusion of privacy in social networks with mixed public and private user profiles , 2009, WWW '09.

[33]  L. Thompson,et al.  Social Utility and Decision Making in Interpersonal Contexts , 1989 .

[34]  Jennifer Golbeck,et al.  Predicting personality with social media , 2011, CHI Extended Abstracts.

[35]  Reza Zafarani,et al.  Connecting users across social media sites: a behavioral-modeling approach , 2013, KDD.

[36]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[37]  Huan Liu,et al.  Relational learning via latent social dimensions , 2009, KDD.

[38]  Jure Leskovec,et al.  The dynamics of viral marketing , 2005, EC '06.

[39]  Christopher Krügel,et al.  A Practical Attack to De-anonymize Social Network Users , 2010, 2010 IEEE Symposium on Security and Privacy.

[40]  Hugo Liu InterestMap : Harvesting Social Network Profiles for Recommendations , 2004 .

[41]  T. Graepel,et al.  Private traits and attributes are predictable from digital records of human behavior , 2013, Proceedings of the National Academy of Sciences.

[42]  Balachander Krishnamurthy,et al.  On the leakage of personally identifiable information via online social networks , 2009, CCRV.

[43]  David S. Rosenblum,et al.  What Anyone Can Know: The Privacy Risks of Social Networking Sites , 2007, IEEE Security & Privacy.

[44]  Huan Liu,et al.  Exploiting vulnerability to secure user privacy on a social networking site , 2011, KDD.

[45]  Sharad Goel,et al.  Who Does What on the Web: A Large-Scale Study of Browsing Behavior , 2012, ICWSM.

[46]  E. David,et al.  Networks, Crowds, and Markets: Reasoning about a Highly Connected World , 2010 .

[47]  H. R. Beech,et al.  Social Interaction , 1970, Encyclopedia of Social Network Analysis and Mining.

[48]  Danah Boyd,et al.  Social Network Sites: Definition, History, and Scholarship , 2007, J. Comput. Mediat. Commun..

[49]  William A. Brock,et al.  Discrete Choice with Social Interactions , 2001 .

[50]  Kristen LeFevre,et al.  Privacy wizards for social networking sites , 2010, WWW '10.

[51]  Vitaly Shmatikov,et al.  De-anonymizing Social Networks , 2009, 2009 30th IEEE Symposium on Security and Privacy.

[52]  S. Gosling,et al.  PERSONALITY PROCESSES AND INDIVIDUAL DIFFERENCES The Do Re Mi’s of Everyday Life: The Structure and Personality Correlates of Music Preferences , 2003 .

[53]  Bobby Bhattacharjee,et al.  Persona: an online social network with user-defined privacy , 2009, SIGCOMM '09.

[54]  Jiawei Han,et al.  ACM Transactions on Knowledge Discovery from Data: Introduction , 2007 .

[55]  Hua Li,et al.  Demographic prediction based on user's browsing behavior , 2007, WWW '07.

[56]  Vitaly Shmatikov,et al.  Robust De-anonymization of Large Sparse Datasets , 2008, 2008 IEEE Symposium on Security and Privacy (sp 2008).

[57]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.