Incremental <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-Anonymous Microaggregation in Large-Scale Electronic Surveys With Optimized Scheduling

Incremental <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-Anonymous Microaggregation in Large-Scale Electronic Surveys With Optimized Scheduling

Improvements in technology have led to enormous volumes of detailed personal information made available for any number of statistical studies. This has stimulated the need for anonymization techniques striving to attain a difficult compromise between the usefulness of the data and the protection of...

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Bibliographic Details
Main Authors: David Rebollo-Monedero, Cesar Hernandez-Baigorri, Jordi Forne, Miguel Soriano
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Data privacy
statistical disclosure control
<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k</italic>-anonymity
microaggregation
electronic surveys
large-scale datasets
Online Access:https://ieeexplore.ieee.org/document/8491270/

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https://ieeexplore.ieee.org/document/8491270/

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