Differential Privacy-Preserving Density Peaks Clustering Based on Shared Near Neighbors Similarity

Differential Privacy-Preserving Density Peaks Clustering Based on Shared Near Neighbors Similarity

Density peaks clustering is a novel and efficient density-based clustering algorithm. However, the problem of the sensitive information leakage and the associated security risk with the applications of clustering methods is rarely considered. To address the problem, we proposed differential privacy-...

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Bibliographic Details
Main Authors: Liping Sun, Shuting Bao, Shang Ci, Xiaoyao Zheng, Liangmin Guo, Yonglong Luo
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Privacy preservation
differential privacy
density peaks clustering algorithm
shared near neighbors similarity
Online Access:https://ieeexplore.ieee.org/document/8756224/

Internet

https://ieeexplore.ieee.org/document/8756224/

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