Towards Privacy-Preserving Content Sharing for Online Social Networks
Pages 1088 - 1095
Abstract
This paper presents presents an approach to preserve privacy for content sharing in online social networks. The approach is based on the concept of friendship strengths and social ties within a friendship circle. Friends can be categorized into different groups according to social strength e.g., close friends, just friends, and distant friends. Therefore, there are corresponding levels of privacy concerns. The paper describes a mechanism that categorizes a friend list based on "social context," which then allows the user to decide on with which social tie the content ought to be shared.
References
[1]
A. Kazeniac, "Social networks: Facebook takes over top spot, twitter climbs," February 2009. {Online}. Available: http://blog.compete.com/2009/02/09/facebook-myspace-twitter-social-network/
[2]
Twitpic, "twitpic: share photos on twitter," August 2009. {Online}. Available: http://twitpic.com/
[3]
A. Felt and D. Evans, "Privacy protection for social networking platforms," in W2SP 2008: Web 2.0 Security and Privacy 2008. New York, NY, USA: IEEE, 2008, pp. 1--8.
[4]
B. Krishnamurthy and C. E. Wills, "Characterizing privacy in online social networks," in WOSP '08: Proceedings of the first workshop on Online social networks. New York, NY, USA: ACM, 2008, pp. 37--42.
[5]
A. Korolova, R. Motwani, S. U. Nabar, and Y. Xu, "Link privacy in social networks," in CIKM '08: Proceeding of the 17th ACM conference on Information and knowledge management. New York, NY, USA: ACM, 2008, pp. 289--298.
[6]
B. Zhou and J. Pei, "Preserving privacy in social networks against neighborhood attacks," in ICDE '08: Proceedings of the 2008 IEEE 24th International Conference on Data Engineering. Washington, DC, USA: IEEE Computer Society, 2008, pp. 506--515.
[7]
L. Backstrom, C. Dwork, and J. Kleinberg, "Wherefore art thou r3579x?: anonymized social networks, hidden patterns, and structural steganography," in WWW '07: Proceedings of the 16th international conference on World Wide Web. New York, NY, USA: ACM, 2007, pp. 181--190.
[8]
R. Kumar, J. Novak, and A. Tomkins, "Structure and evolution of online social networks," in KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. New York, NY, USA: ACM, 2006, pp. 611--617.
[9]
A. Mislove, M. Marcon, K. P. Gummadi, P. Druschel, and B. Bhattacharjee, "Measurement and analysis of online social networks," in IMC '07: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement. New York, NY, USA: ACM, 2007, pp. 29--42.
[10]
B. Krishnamurthy, P. Gill, and M. Arlitt, "A few chirps about twitter," in WOSP '08: Proceedings of the first workshop on Online social networks. New York, NY, USA: ACM, 2008, pp. 19--24.
[11]
A. Java, X. Song, T. Finin, and B. Tseng, "Why we twitter: understanding microblogging usage and communities," in WebKDD/SNA-KDD '07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis. New York, NY, USA: ACM, 2007, pp. 56--65.
[12]
M. Cha, H. Kwak, P. Rodriguez, Y.-Y. Ahn, and S. Moon, "I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system," in IMC '07: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement. New York, NY, USA: ACM, 2007, pp. 1--14.
[13]
P. Gill, M. Arlitt, Z. Li, and A. Mahanti, "Youtube traffic characterization: a view from the edge," in IMC '07: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement. New York, NY, USA: ACM, 2007, pp. 15--28.
[14]
G. Chen and F. Rahman, "Analyzing privacy designs of mobile social networking applications," in EUC '08: Proceedings of the 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing. Washington, DC, USA: IEEE Computer Society, 2008, pp. 83--88.
[15]
J. Bonneau, J. Anderson, and L. Church, "Privacy suites: shared privacy for social networks," in SOUPS '09: Proceedings of the 5th Symposium on Usable Privacy and Security. New York, NY, USA: ACM, 2009, pp. 1--2.
[16]
S. Preibusch and A. R. Beresford, "Privacy-preserving friendship relations for mobile social networking," in W3C Workshop on the Future of Social Networking. MA, USA: W3C, 2008, pp. 1--5.
[17]
E. Zheleva and L. Getoor, "To join or not to join: the illusion of privacy in social networks with mixed public and private user profiles," in WWW '09: Proceedings of the 18th international conference on World wide web. New York, NY, USA: ACM, 2009, pp. 531--540.
[18]
M. Granovetter, "The strength of weak ties," The American Journal of Sociology, vol. 78, no. 6, pp. 1360--1380, 1973.
[19]
P. V. Marsden and K. E. Campbell, "Measuring tie strength," Social Forces, vol. 63, no. 2, pp. 482--501, December 1984.
[20]
S. Phithakkitnukoon and R. Dantu, "A dimension-reduction framework for human behavioral time series data," in AAAI'09 Spring Symposium on Technosocial Predictive Analytics. AAAI, 2009, pp. 95--101.
Index Terms
- Towards Privacy-Preserving Content Sharing for Online Social Networks
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October 2018
1881 pages
ISBN:9781450359665
DOI:10.1145/3267305
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Published: 08 October 2018
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UbiComp '18: The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing
October 8 - 12, 2018
Singapore, Singapore
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Overall Acceptance Rate 764 of 2,912 submissions, 26%
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