A Review on Privacy Preservation of Social Networks Using Graphs-Reference-Cited by-同舟云学术

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A Review on Privacy Preservation of Social Networks Using Graphs

Published:2020-04-23 Issue:2 Volume:16 Page:190-223
ISSN:1936-1610
Container-title:Journal of Applied Security Research
language:en
Short-container-title:Journal of Applied Security Research

Author:

Kiranmayi M.¹,Maheswari N.¹

Affiliation:

1. School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India

Publisher

Informa UK Limited

Subject

Law,Safety Research,Safety, Risk, Reliability and Quality,Education

Link

https://www.tandfonline.com/doi/pdf/10.1080/19361610.2020.1751558

Reference92 articles.

1. Publishing Social Network Graph Eigenspectrum With Privacy Guarantees

2. Assam, R., Hassani, M., Brysch, M. & Seidl, T. (2014, June 30–July 2). (k, d)-core anonymity: Structural anonymization of massive network [Paper presentation]. 26th International Conference on Scientific and Statistical Database Management, Santa Cruz, CA, USA.

3. Class-based graph anonymization for social network data

4. Securing Social Network Graph against Structural Attack based on Ant Colony Optimization

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1. Privacy‐preserving graph publishing with disentangled variational information bottleneck;Concurrency and Computation: Practice and Experience;2023-12-12

2. Entropy-driven differential privacy protection scheme based on social graphlet attributes;The Journal of Supercomputing;2023-11-07

3. Private Graph Data Release: A Survey;ACM Computing Surveys;2023-02-22

4. Differential privacy protection scheme based on community density aggregation and matrix perturbation;Information Sciences;2022-11

5. Differential Privacy: An Umbrella Review;Artificial Intelligence and Cybersecurity;2022-08-01

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