Loading [MathJax]/extensions/MathMenu.js
Applications of Differential Privacy in Social Network Analysis: A Survey | IEEE Journals & Magazine | IEEE Xplore

Applications of Differential Privacy in Social Network Analysis: A Survey


Abstract:

Differential privacy provides strong privacy preservation guarantee in information sharing. As social network analysis has been enjoying many applications, it opens a new...Show More

Abstract:

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.
Published in: IEEE Transactions on Knowledge and Data Engineering ( Volume: 35, Issue: 1, 01 January 2023)
Page(s): 108 - 127
Date of Publication: 13 April 2021

ISSN Information:

Funding Agency:


Contact IEEE to Subscribe

References

References is not available for this document.