Achieve data privacy and clustering accuracy simultaneously through quantized data recovery

Achieve data privacy and clustering accuracy simultaneously through quantized data recovery

Abstract This paper develops a data collection and processing framework that achieves individual users’ data privacy and the operator’s information accuracy simultaneously. Data privacy is enhanced by adding noise and applying quantization to the data before transmission, and the privacy of an indiv...

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Bibliographic Details
Main Authors: Ren Wang, Meng Wang, Jinjun Xiong
Format: Article
Language:English
Published: SpringerOpen 2020-05-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Subspace clustering
Quantization
Data recovery
Data privacy
Smart meter
Online Access:http://link.springer.com/article/10.1186/s13634-020-00682-7

Internet

http://link.springer.com/article/10.1186/s13634-020-00682-7

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