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Locally differentially private distributed algorithms for set intersection and union

delete2021-05-13
delete4
PRE
AI
Q
Qiao Xue
朱友文 (Youwen Zhu) *
J
Jian Wang
X
Xingxin Li
J
Ji Zhang
DOI:10.1007/s11432-018-9899-8delete
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Abstract

Abstract

En 中文
Conclusion This study designed schemes to obtain distributed multiset intersection and union by exploiting LDP. In the schemes, the private items in each data owner's set were sanitized to satisfy epsilon-LDP, and meanwhile the collector could derive a high-accuracy intersection and union from noisy sets. Through theoretical analysis and experiments, we presented that the proposed schemes enjoy good utility and strong robustness.
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Journal

Science China Information Sciences cover
Science China Information Sciences
IF:
7.6
Papers:
4.9K
Citations:
8.9K

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U
University of Southern Queensland
Scholars:
4.1K
Papers: 4.8K
Citations: 18