Local Differential Privately Anonymizing Online Social Networks Under HRG-Based Model.

IEEE Transactions on Computational Social Systems(2018)

引用 33|浏览9
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摘要
Following the trend of online social networks (OSNs) data sharing and publishing, users raise serious concerns on OSN privacy. Differential privacy is a mechanism to anonymize sensitive data. It employs graph abstraction models, such as the hierarchical random graph (HRG) model, to extract graph features and then add sufficient noise. However, the noise amount, determined by the sensitivity, is us...
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关键词
Privacy,Social network services,Feature extraction,Network topology,Sensitivity,Probability
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