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De-anonymizing social graphs via node similarity

Published: 07 April 2014 Publication History

Abstract

Recently, a number of anonymization algorithms have been developed to protect the privacy of social graph data. However, in order to satisfy higher level of privacy requirements, it is sometimes impossible to maintain sufficient utility. Is it really easy to de-anonymize "lightly" anonymized social graphs? Here "light" anonymization algorithms stand for those algorithms that maintain higher data utility. To answer this question, we proposed a de-anonymization algorithm based on a node similarity measurement. Using the proposed algorithm, we evaluated the privacy risk of several "light" anonymization algorithms on real datasets.

References

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L. Backstrom, C. Dwork, and J. Kleinberg. Wherefore art thou r3579x?: anonymized social networks, hidden patterns, and structural steganography. In Proceedings of the 16th International Conference on World Wide Web (WWW 2007), pages 181--190, 2007.
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F. Bonchi, A. Gionis, and T. Tassa. Identity obfuscation in graphs through the information theoretic lens. In Proceedings of 27th International Conference on Data Engineering (ICDE 2011), pages 924--935, 2011.
[3]
M. Hay, G. Miklau, D. Jensen, D. Towsley, and P. Weis. Resisting structural re-identification in anonymized social networks. Proc. VLDB Endow., 1(1):102--114, 2008.
[4]
K. Liu and E. Terzi. Towards identity anonymization on graphs. In Proceedings of the 2008 ACM International Conference on Management of Data (SIGMOD 2008), pages 93--106, New York, NY, USA.
[5]
A. Narayanan and V. Shmatikov. De-anonymizing social networks. In Proceedings of the 2009 IEEE Symposium on Security and Privacy, pages 173--187, May 2009.

Cited By

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  • (2020)Security and Privacy in Social Networks: Data and Structural AnonymityHandbook of Computer Networks and Cyber Security10.1007/978-3-030-22277-2_11(265-293)Online publication date: 1-Jan-2020
  • (2018)Structure Based User Identification across Social NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.278443030:6(1178-1191)Online publication date: 1-Jun-2018
  • (2018)An unsupervised user identification algorithm using network embedding and scalable nearest neighbourCluster Computing10.1007/s10586-018-1940-622:S4(8677-8687)Online publication date: 28-Feb-2018
  • Show More Cited By

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Published In

cover image ACM Other conferences
WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web
April 2014
1396 pages
ISBN:9781450327459
DOI:10.1145/2567948
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

  • IW3C2: International World Wide Web Conference Committee

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 April 2014

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Author Tags

  1. de-anonymization
  2. privacy protection
  3. social network

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  • Poster

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WWW '14
Sponsor:
  • IW3C2

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

View all
  • (2020)Security and Privacy in Social Networks: Data and Structural AnonymityHandbook of Computer Networks and Cyber Security10.1007/978-3-030-22277-2_11(265-293)Online publication date: 1-Jan-2020
  • (2018)Structure Based User Identification across Social NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.278443030:6(1178-1191)Online publication date: 1-Jun-2018
  • (2018)An unsupervised user identification algorithm using network embedding and scalable nearest neighbourCluster Computing10.1007/s10586-018-1940-622:S4(8677-8687)Online publication date: 28-Feb-2018
  • (2015)Effective Social Graph Deanonymization Based on Graph Structure and Descriptive InformationACM Transactions on Intelligent Systems and Technology10.1145/27008366:4(1-29)Online publication date: 13-Jul-2015
  • (2015)Discovering missing me edges across social networksInformation Sciences: an International Journal10.1016/j.ins.2015.05.014319:C(18-37)Online publication date: 20-Oct-2015

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