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Applications of Differential Privacy in Social Network Analysis: A Survey

Publication ,  Journal Article
Jiang, H; Pei, J; Yu, D; Yu, J; Gong, B; Cheng, X
Published in: IEEE Transactions on Knowledge and Data Engineering
January 1, 2023

Differential privacy provides strong privacy preservation guarantee in information sharing. As social network analysis has been enjoying many applications, it opens a new arena for applications of differential privacy. This article presents a comprehensive survey connecting the basic principles of differential privacy and applications in social network analysis. We concisely review the foundations of differential privacy and the major variants. Then, we discuss how differential privacy is applied to social network analysis, including privacy attacks in social networks, models of differential privacy in social network analysis, and a series of popular tasks, such as analyzing degree distribution, counting subgraphs and assigning weights to edges. We also discuss a series of challenges for future work.

Duke Scholars

Published In

IEEE Transactions on Knowledge and Data Engineering

DOI

EISSN

1558-2191

ISSN

1041-4347

Publication Date

January 1, 2023

Volume

35

Issue

1

Start / End Page

108 / 127

Related Subject Headings

  • Information Systems
  • 46 Information and computing sciences
  • 08 Information and Computing Sciences
 

Citation

APA
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ICMJE
MLA
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Jiang, H., Pei, J., Yu, D., Yu, J., Gong, B., & Cheng, X. (2023). Applications of Differential Privacy in Social Network Analysis: A Survey. IEEE Transactions on Knowledge and Data Engineering, 35(1), 108–127. https://doi.org/10.1109/TKDE.2021.3073062
Jiang, H., J. Pei, D. Yu, J. Yu, B. Gong, and X. Cheng. “Applications of Differential Privacy in Social Network Analysis: A Survey.” IEEE Transactions on Knowledge and Data Engineering 35, no. 1 (January 1, 2023): 108–27. https://doi.org/10.1109/TKDE.2021.3073062.
Jiang H, Pei J, Yu D, Yu J, Gong B, Cheng X. Applications of Differential Privacy in Social Network Analysis: A Survey. IEEE Transactions on Knowledge and Data Engineering. 2023 Jan 1;35(1):108–27.
Jiang, H., et al. “Applications of Differential Privacy in Social Network Analysis: A Survey.” IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 1, Jan. 2023, pp. 108–27. Scopus, doi:10.1109/TKDE.2021.3073062.
Jiang H, Pei J, Yu D, Yu J, Gong B, Cheng X. Applications of Differential Privacy in Social Network Analysis: A Survey. IEEE Transactions on Knowledge and Data Engineering. 2023 Jan 1;35(1):108–127.

Published In

IEEE Transactions on Knowledge and Data Engineering

DOI

EISSN

1558-2191

ISSN

1041-4347

Publication Date

January 1, 2023

Volume

35

Issue

1

Start / End Page

108 / 127

Related Subject Headings

  • Information Systems
  • 46 Information and computing sciences
  • 08 Information and Computing Sciences