Privacy preserving anomaly detection based on local density estimation

Privacy preserving anomaly detection based on local density estimation

Anomaly detection has been widely researched in financial, biomedical and other areas. However, most existing algorithms have high time complexity. Another important problem is how to efficiently detect anomalies while protecting data privacy. In this paper, we propose a fast anomaly detection algor...

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Bibliographic Details
Main Authors: Chunkai Zhang, Ao Yin, Wei Zuo, Yingyang Chen
Format: Article
Language:English
Published: AIMS Press 2020-05-01
Series:Mathematical Biosciences and Engineering
Subjects:
anomaly detection
local density
privacy protection
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2020196?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2020196?viewType=HTML

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