Encyclopedia of Social Network Analysis and Mining

2014 Edition
| Editors: Reda Alhajj, Jon Rokne

Anonymization and De-anonymization of Social Network Data

  • Sean Chester
  • Bruce M. Kapron
  • Gautam Srivastava
  • Venkatesh Srinivasan
  • Alex Thomo
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6170-8_22


Adversarial knowledge; Anonymity; Complexity; Graph algorithms; Privacy breach; Social network privacy



Somebody who attempts to reveal sensitive, private information

Adversarial Model

Formal description of the unique characteristics of a particular adversary

Attribute Disclosure

A privacy breach wherein some descriptive attribute of somebody is revealed

Identity Disclosure

A privacy breach in which a presumably anonymous person is in fact identifiable


A condition under which any instance of P appears at least k times


The particular social network member against whom an adversary is trying to breach privacy


As social networks grow and become increasingly pervasive, so too do the opportunities to analyze the data that arises from them. Social network data can be released for public research that can lead to breakthroughs in fields as diverse as marketing and health care. But with the release of data come questions of privacy. Is...

This is a preview of subscription content, log in to check access.


  1. Aggarwal G, Feder T, Kenthapadi K, Motwani R, Panigrahy R, Thomas D, Zhu A (2005) Anonymizing tables. In: Proceedings of the ICDT, Edinburgh, pp 246–258Google Scholar
  2. Backstrom L, Dwork C, Kleinberg JM (2007) Wherefore art thou r3579x?: anonymized social networks, hidden patterns, and structural steganography. In: Proceedings of the WWW, Banff, pp 181–190Google Scholar
  3. Boldi P, Bonchi F, Gionis A, Tassa T (2012) Injecting uncertainty in graphs for identity obfuscation. PVLDB 5(11):1376–1387Google Scholar
  4. Bonizzoni P, Vedova GD, Dondi R (2009) The k-anonymity problem is hard. In: Proceedings of the FCT, Wroclaw, pp 26–37Google Scholar
  5. Casas-Roma J, Herrera-Joancomart J, Torra V (2012) Comparing random-based and k-anonymity-based algorithms for graph anonymization. In: Proceedings of the MDAI, Girona. Springer, pp 197–209Google Scholar
  6. Cheng J, Fu AW-C, Liu J (2010) K-isomorphism: privacy preserving network publication against structural attacks. In: Proceedings of the SIGMOD, Indianapolis, pp 459–470Google Scholar
  7. Chester S, Srivastava G (2011) Social network privacy for attribute disclosure attacks. In: Proceedings of the ASONAM, Kaohsiung, pp 445–449Google Scholar
  8. Chester S, Gaertner J, Stege U, Venkatesh S (2012a) Anonymizing subsets of social networks with degree constrained subgraphs. In: Proceedings of the ASONAM, Istanbul, pp 418–422Google Scholar
  9. Chester S, Kapron BM, Ramesh G, Srivastava G, Thomo A, Venkatesh S (2012b) Why Waldo befriended the dummy? k-anonymization of social networks with pseudo-nodes. Soc Netw Anal Min, 3(3):381–399Google Scholar
  10. Chester S, Kapron BM, Srivastava G, Venkatesh S (2012c) Complexity of social network anonymization. Soc Netw Anal Min, 3(2):151–166Google Scholar
  11. Dwork C (2008) Differential privacy: a survey of results. In: Proceedings of the TAMC, Xi'an, pp 1–19Google Scholar
  12. Erdos P, Gallai T (1960) Gráfok elöírt fokszámú pontokkal. Matematikai Lapok 11:264–274Google Scholar
  13. Hay M, Miklau G, Jensen D, Weis P, Srivastava S (2007) Anonymizing social networks. Amherst technical report, University of MassachusettsGoogle Scholar
  14. Hay M, Li C, Miklau G, Jensen D (2009) Accurate estimation of the degree distribution of private networks. In: Proceedings of the ICDM 2009, Miami, pp 169–178Google Scholar
  15. Karwa V, Raskhodnikova S, Smith A, Yaroslavtsev G (2011) Private analysis of graph structure. PVLDB 4(11):1146–1157Google Scholar
  16. Kasiviswanathan SP, Nissim K, Raskhodnikova S, Smith A (2013) Analyzing graphs with node differential privacy. In: Proceedings of the TCC, Tokyo, pp 457–476Google Scholar
  17. Li N, Li T, Venkatasubramanian S (2007) t-closeness: privacy beyond k-anonymity and l-diversity. In: Proceedings of the ICDE, Istanbul, pp 106–115Google Scholar
  18. Lui K, Terzi E (2008) Towards identity anonymization on graphs. In: Proceedings of the SIGMOD, Vancouver, pp 93–106Google Scholar
  19. Machanavajjhala A, Kifer D, Gehrke J, Venkitasubramaniam M (2007) L-diversity: privacy beyond k-anonymity. TKDD 1(1):52Google Scholar
  20. Meyerson A, Williams R (2004) On the complexity of optimal K-anonymity. In: Proceedings of the PODS, Paris, pp 223–228Google Scholar
  21. Narayanan A, Shmatikov V (2009) De-anonymizing social networks. In: Proceedings of IEEE symposium on security and privacy, Oakland, pp 173–187Google Scholar
  22. Nissim K, Raskhodnikova S, Smith A (2007) Smooth sensitivity and sampling in private data analysis. In: Proceedings of the STOC, San Diego, pp 75–84Google Scholar
  23. Srivatsa M, Hicks M (2012) Deanonymizing mobility traces: using social network as a side-channel. In: Proceedings of the ACM conference on computer and communications security, Raleigh, pp 628–637Google Scholar
  24. Sweeney L (2002) k-anonymity: a model for protecting privacy. Int J Uncertain Fuzziness Knowl Based Syst 10(5):557–570zbMATHMathSciNetGoogle Scholar
  25. Thompson B, Yao D (2009) The union-split algorithm and cluster-based anonymization of social networks. In: Proceedings of the ASIACCS, Sydney, pp 218–227Google Scholar
  26. Wu W, Xiao Y, Wang W, He Z, Wang Z (2010) k-symmetry model for identity anonymization in social networks. In: Proceedings of the EDBT, Lausanne, pp 111–122Google Scholar
  27. Ying X, Pan K, Wu X, Guo L (2009) Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing. In: Proceedings of the SNA-KDD, Paris. Article #10, 10 pagesGoogle Scholar
  28. Zhou B, Pei J (2008) Preserving privacy in social networks against neighborhood attacks. In: Proceedings of the ICDE, Cancun, pp 506–515Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Sean Chester
    • 1
  • Bruce M. Kapron
    • 1
  • Gautam Srivastava
    • 1
  • Venkatesh Srinivasan
    • 1
  • Alex Thomo
    • 1
  1. 1.Department of Computer Science, University of VictoriaVictoriaCanada