Skip to main content

Privacy Issues in Social Networks: A Brief Survey

  • Conference paper

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 300))

Abstract

Most social networks allow individuals to share their information with friends but also with unknown people. Therefore, in order to prevent unauthorized access to sensitive, private information, the study of privacy issues in social networks has become an important task. This paper provides a brief overview of the emerging research in privacy issues in social networks.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adamic, L.A., Adar, E.: Friends and neighbors on the web. Social networks 25(3), 211–230 (2003)

    Article  Google Scholar 

  2. Aggarwal, C.C., Yu, P.S.: An introduction to privacy-preserving data mining. In: Privacy-Preserving Data Mining, pp. 1–9 (2008)

    Google Scholar 

  3. Beach, A., Gartrell, M., Han, R.: q-anon: Rethinking anonymity for social networks. In: Elmagarmid, A.K., Agrawal, D. (eds.) SocialCom/PASSAT, pp. 185–192. IEEE Computer Society (2010)

    Google Scholar 

  4. Beach, A., Gartrell, M., Han, R.: Social-K: Real-time K-anonymity guarantees for social network applications. In: 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 600–606. IEEE ( March 2010)

    Google Scholar 

  5. Cartwright, D.: Achieving change in people: Some applications of group dynamics theory. Human Relations 4(4), 381–392 (1951)

    Article  Google Scholar 

  6. Cartwright, D., Harary, F.: Structural balance: a generalization of heider’s theory. Psychological Review 63(5), 277 (1956)

    Article  Google Scholar 

  7. Deutsch, K.W.: On communication models in the social sciences. Public Opinion Quarterly 16(3), 356–380 (1952)

    Article  Google Scholar 

  8. Díaz, I., Ranilla, J., Rodríguez-Muniz, L.J., Troiano, L.: Identifying the Risk of Attribute Disclosure by Mining Fuzzy Rules. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds.) IPMU 2010. CCIS, vol. 80, pp. 455–464. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  9. Díaz, I., Rodríguez-Muñiz, L.J., Troiano, L.: Fuzzy sets in data protection: strategies and cardinalities. Logic Journal of IGPL (2011)

    Google Scholar 

  10. Domingo-Ferrer, J., Torra, V.: On the connections between statistical disclosure control for microdata and some artificial intelligence tools. Inf. Sci. Inf. Comput. Sci. 151, 153–170 (2003)

    MATH  Google Scholar 

  11. Dwork, C.: Differential Privacy. In: Bugliesi, M., Preneel, B., Sassone, V., Wegener, I. (eds.) ICALP 2006. LNCS, vol. 4052, pp. 1–12. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  12. Dwork, C.: Differential Privacy: A Survey of Results. In: Agrawal, M., Du, D.-Z., Duan, Z., Li, A. (eds.) TAMC 2008. LNCS, vol. 4978, pp. 1–19. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  13. Dwyer, C., Hiltz, S.R., Passerini, K.: Trust and privacy concern within social networking sites: A comparison of facebook and myspace. In: Proceedings of the Thirteenth Americas Conference on Information Systems (AMCIS 2007) (2007) Paper 339

    Google Scholar 

  14. Fang, C., Kohram, M., Ralescu, A.: Towards a spectral regression with low-rank approximation approach for link prediction in dynamic graphs. IEEE Intelligent Systems 99, 1

    Google Scholar 

  15. Hanneman, R.A., Riddle, M.: Introduction to social network methods. University of California, Riverside (2005)

    Google Scholar 

  16. Heider, F.: Attitudes and cognitive organization. The Journal of Psychology 21(1), 107–112 (1946)

    Article  Google Scholar 

  17. Holsheimer, M., Siebes, A.P.J.M.: Data mining: the search for knowledge in databases. Technical report, Amsterdam, The Netherlands, The Netherlands (1994)

    Google Scholar 

  18. Jamali, M., Abolhassani, H.: Different aspects of social network analysis. In: IEEE/WIC/ACM International Conference on Web Intelligence, WI 2006, pp. 66–72 (December 2006)

    Google Scholar 

  19. Katz, L.: A new status index derived from sociometric analysis. Psychometrika 18(1), 39–43 (1953)

    Article  MATH  Google Scholar 

  20. Korolova, A., Motwani, R., Nabar, S.U., Xu, Y.: Link privacy in social networks. In: Proceeding of the 17th ACM Conference on Information and Knowledge Management, pp. 289–298. ACM (2008)

    Google Scholar 

  21. Laird, P.D.: Learning from good and bad data. Kluwer Academic Publishers, Norwell (1988)

    Book  MATH  Google Scholar 

  22. Leicht, E.A., Holme, P., Newman, M.E.J.: Vertex similarity in networks. Physical Review E 73(2), 26120 (2006)

    Article  Google Scholar 

  23. Leontief, W.W.: The structure of American economy, 1919-1939: An empirical application of equilibrium analysis. Oxford University Press, New York (1951)

    Google Scholar 

  24. Li, N., Li, T.: t-closeness: Privacy beyond k-anonymity and?-diversity. In: Proceedings of IEEE International Conference on Data Engineering (2007)

    Google Scholar 

  25. Li, N., Li, T., Venkatasubramanian, S.: t-closeness: Privacy beyond k-anonymity and l-diversity. In: ICDE, pp. 106–115 (2007)

    Google Scholar 

  26. Liben-Nowell, D., Kleinberg, J.: The link-prediction problem for social networks. Journal of the American society for information science and technology 58(7), 1019–1031 (2007)

    Article  Google Scholar 

  27. Liu, K., Das, K., Grandison, T., Kargupta, H.: Privacy-preserving data analysis on graphs and social networks

    Google Scholar 

  28. Loukides, G., Shao, J.: Preventing range disclosure in k-anonymised data. Expert Syst. Appl. 38(4), 4559–4574 (2011)

    Article  Google Scholar 

  29. Lovász, L.: Random walks on graphs: A survey. Combinatorics, Paul Erdos is Eighty 2(1), 1–46 (1993)

    Google Scholar 

  30. Machanavajjhala, A., Gehrke, J., Kifer, D., Venkitasubramaniam, M.: l-diversity: Privacy beyond k-anonymity. In: 22nd IEEE International Conference on Data Engineering (2006)

    Google Scholar 

  31. Samarati, P.: Protecting respondents’ identities in microdata release. IEEE Transactions on Knowledge and Data Engineering 13, 1010–1027 (2001)

    Article  Google Scholar 

  32. Sarathy, R., Muralidhar, K.: Evaluating laplace noise addition to satisfy differential privacy for numeric data. Transactions on Data Privacy 4(1), 1–17 (2011)

    MathSciNet  Google Scholar 

  33. Facebook Statistics, www.facebook.com/press/info.php?statistics

  34. Sweeney, L.: k-anonymity: a model for protecting privacy. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems 10(5), 557–570 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  35. Ying, X., Wu, X.: On Link Privacy in Randomizing Social Networks. In: Theeramunkong, T., Kijsirikul, B., Cercone, N., Ho, T.-B. (eds.) PAKDD 2009. LNCS, vol. 5476, pp. 28–39. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  36. Zheleva, E., Getoor, L.: To join or not to join: the illusion of privacy in social networks with mixed public and private user profiles. In: Proceedings of the 18th International Conference on World Wide Web, pp. 531–540. ACM (2009)

    Google Scholar 

  37. Zhou, B., Pei, J.: The k-anonymity and l-diversity approaches for privacy preservation in social networks against neighborhood attacks. Knowledge and Information Systems 28(1), 1–38 (2010)

    MathSciNet  Google Scholar 

  38. Zhou, B., Pei, J., Luk, W.: A brief survey on anonymization techniques for privacy preserving publishing of social network data. SIGKDD Explor. Newsl. 10, 12–22 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Díaz, I., Ralescu, A. (2012). Privacy Issues in Social Networks: A Brief Survey. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 300. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31724-8_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-31724-8_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31723-1

  • Online ISBN: 978-3-642-31724-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics