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Privacy in dynamic social networks

Published: 26 April 2010 Publication History

Abstract

Anonymization of social networks before they are published or shared has become an important research question. Recent work on anonymizing social networks has looked at privacy preserving techniques for publishing a single instance of the network. However, social networks evolve and a single instance is inadequate for analyzing the evolution of the social network or for performing any longitudinal data analysis. We study the problem of repeatedly publishing social network data as the network evolves, while preserving privacy of users. Publishing multiple instances of the same network independently has privacy risks, since stitching the information together may allow an adversary to identify users in the networks.
We propose methods to anonymize a dynamic network such that the privacy of users is preserved when new nodes and edges are added to the published network. These methods make use of link prediction algorithms to model the evolution of the social network. Using this predicted graph to perform group-based anonymization, the loss in privacy caused by new edges can be reduced. We evaluate the privacy loss on publishing multiple social network instances using our methods.

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S. Bhagat, G. Cormode, B. Krishnamurthy, and D. Srivastava. Prediction provides privacy in dynamic social networks. Manuscript, 2010.
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Cited By

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  • (2025)Dynamic Privacy Protection with Large Language Model in Social NetworksAlgorithms and Architectures for Parallel Processing10.1007/978-981-96-1545-2_14(228-248)Online publication date: 13-Feb-2025
  • (2023)A Tale of Two Cultures: Comparing Interpersonal Information Disclosure Norms on TwitterProceedings of the ACM on Human-Computer Interaction10.1145/36100457:CSCW2(1-40)Online publication date: 4-Oct-2023
  • (2023)Inferring links in directed complex networks through feed forward loop motifsHumanities and Social Sciences Communications10.1057/s41599-023-01863-z10:1Online publication date: 29-Jun-2023
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Published In

cover image ACM Other conferences
WWW '10: Proceedings of the 19th international conference on World wide web
April 2010
1407 pages
ISBN:9781605587998
DOI:10.1145/1772690

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2010

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Author Tags

  1. dynamic networks
  2. privacy
  3. re-publication

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WWW '10
WWW '10: The 19th International World Wide Web Conference
April 26 - 30, 2010
North Carolina, Raleigh, USA

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

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Cited By

View all
  • (2025)Dynamic Privacy Protection with Large Language Model in Social NetworksAlgorithms and Architectures for Parallel Processing10.1007/978-981-96-1545-2_14(228-248)Online publication date: 13-Feb-2025
  • (2023)A Tale of Two Cultures: Comparing Interpersonal Information Disclosure Norms on TwitterProceedings of the ACM on Human-Computer Interaction10.1145/36100457:CSCW2(1-40)Online publication date: 4-Oct-2023
  • (2023)Inferring links in directed complex networks through feed forward loop motifsHumanities and Social Sciences Communications10.1057/s41599-023-01863-z10:1Online publication date: 29-Jun-2023
  • (2022)The Dynamic Privacy-Preserving Mechanisms for Online Dynamic Social NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.301583534:6(2962-2974)Online publication date: 1-Jun-2022
  • (2021)A User-Centric Mechanism for Sequentially Releasing Graph Datasets under Blowfish PrivacyACM Transactions on Internet Technology10.1145/343150121:1(1-25)Online publication date: 17-Feb-2021
  • (2021)Degree Histogram Publishing Method of Dynamic Graph Data Based on Node Differential Privacy2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI)10.1109/CISAI54367.2021.00088(422-429)Online publication date: Sep-2021
  • (2020)Differential Privacy for Evolving Network Based on GHRGMathematical Problems in Engineering10.1155/2020/67839492020(1-12)Online publication date: 3-Dec-2020
  • (2019)Moving Beyond Set-It-And-Forget-It Privacy Settings on Social MediaProceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security10.1145/3319535.3354202(991-1008)Online publication date: 6-Nov-2019
  • (2019)Tracking Community Consistency in Dynamic Networks: An Influence-based ApproachIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2019.2933516(1-1)Online publication date: 2019
  • (2019)Modeling Large-Scale Dynamic Social Networks via Node EmbeddingsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.287260231:10(1994-2007)Online publication date: 1-Oct-2019
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