Correlated Differential Privacy: Hiding Information in Non-IID Data Set

@article{Zhu2015CorrelatedDP,
  title={Correlated Differential Privacy: Hiding Information in Non-IID Data Set},
  author={Tianqing Zhu and Ping Xiong and Gang Li and Wanlei Zhou},
  journal={IEEE Transactions on Information Forensics and Security},
  year={2015},
  volume={10},
  pages={229-242}
}
Privacy preserving on data mining and data release has attracted an increasing research interest over a number of decades. Differential privacy is one influential privacy notion that offers a rigorous and provable privacy guarantee for data mining and data release. Existing studies on differential privacy assume that in a data set, records are sampled independently. However, in real-world applications, records in a data set are rarely independent. The relationships among records are referred to… CONTINUE READING
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