A Targeted Privacy-Preserving Data Publishing Method Based on Bayesian Network
Privacy-preserving data publishing (PPDP) is an essential prerequisite for data-driven AI technologies, (such as data mining, machine learning, deep learning, etc.) to extract knowledge from data safely and legally. It has, as it should be, been studied and explored as a hot topic in the last decade...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9866746/ |