Wdt-SCAN: Clustering decentralized social graphs with local differential privacy-Reference-Cited by-同舟云学术

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Wdt-SCAN: Clustering decentralized social graphs with local differential privacy

Published:2023-02 Issue: Volume:125 Page:103036
ISSN:0167-4048
Container-title:Computers & Security
language:en
Short-container-title:Computers & Security

Author:

Hou Lihe^ORCID,Ni Weiwei,Zhang Sen,Fu Nan^ORCID,Zhang Dongyue^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference30 articles.

1. Emergence of scaling in random networks;Barabasi;Science,1999

2. Local, private, efficient protocols for succinct histograms;Bassily,2015

3. The Johnson-Lindenstrauss transform itself preserves differential privacy;Blocki,2012

4. Differential privacy and robust statistics;Dwork,2009

5. Calibrating noise to sensitivity in private data analysis;Dwork,2006

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1. Locally differentially private graph learning on decentralized social graph;Knowledge-Based Systems;2024-11

2. Trustworthy decentralization based on blockchain tools for social network architectures;Social Network Analysis and Mining;2024-05-10

3. Community detection in decentralized social networks with local differential privacy;Information Sciences;2024-03

4. A clustering-based differential privacy protection algorithm for weighted social networks;Mathematical Biosciences and Engineering;2024

5. Differential privacy in edge computing-based smart city Applications:Security issues, solutions and future directions;Array;2023-09

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