Developments and Applications of Data Deidentification Technology under Big Data

In this age characterized by rapid growth in the volume of data,data deidentification technologies have become crucial in facilitating the analysis of sensitive information.For instance,healthcare information must be processed through deidentification procedures before being passed to data analysis...

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Veröffentlicht in:电子科技学刊 2017-09, Vol.15 (3), p.231-239
Hauptverfasser: Hung-Li Chen, Yao-Tung Tsou, Bo-Chen Tai, Szu-Chuang Li, Yen-Nun Huang, Chia-Mu Yu, Yu-Shian Chiu
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container_issue 3
container_start_page 231
container_title 电子科技学刊
container_volume 15
creator Hung-Li Chen
Yao-Tung Tsou
Bo-Chen Tai
Szu-Chuang Li
Yen-Nun Huang
Chia-Mu Yu
Yu-Shian Chiu
description In this age characterized by rapid growth in the volume of data,data deidentification technologies have become crucial in facilitating the analysis of sensitive information.For instance,healthcare information must be processed through deidentification procedures before being passed to data analysis agencies in order to prevent any exposure of personal details that would violate privacy.As such,privacy protection issues associated with the release of data and data mining have become a popular field of study in the domain of big data.As a strict and verifiable definition of privacy,differential privacy has attracted noteworthy attention and widespread research in recent years.In this study,we analyze the advantages of differential privacy protection mechanisms in comparison to traditional deidentification data protection methods.Furthermore,we examine and analyze the basic theories of differential privacy and relevant studies regarding data release and data mining.
doi_str_mv 10.11989/JEST.1674-862X.60804064
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title Developments and Applications of Data Deidentification Technology under Big Data
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