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Preserving Differential Privacy in Degree-Correlation based Graph Generation
Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as cluster coefficient often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we...
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| Main Authors: | , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3979555/ https://ncbi.nlm.nih.gov/pubmed/24723987 |
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