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dK-Microaggregation: Anonymizing Graphs with Differential Privacy Guarantees

With the advances of graph analytics, preserving privacy in publishing graph data becomes an important task. However, graph data is highly sensitive to structural changes. Perturbing graph data for achieving differential privacy inevitably leads to inject a large amount of noise and the utility of a...

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Detalhes bibliográficos
Publicado no:Advances in Knowledge Discovery and Data Mining
Main Authors: Iftikhar, Masooma, Wang, Qing, Lin, Yu
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7206283/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-47436-2_15
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