Quantifying the Vulnerability of Attributes for Effective Privacy Preservation Using Machine Learning

Personal data have been increasingly used in data-driven applications to improve quality of life. However, privacy preservation of personal data while sharing it with analysts/ researchers has become an essential requirement to be met by data owners (hospitals, banks, insurance companies, etc.). The...

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Hlavní autoři:	Abdul Majeed, Seong Oun Hwang
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2023-01-01
Edice:	IEEE Access
Témata:	Personal data privacy utility anonymization vulnerability machine learning
On-line přístup:	https://ieeexplore.ieee.org/document/10011406/
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