When Poor-Quality Data Meet Anonymization Models: Threats and Countermeasures
In the modern era, the avenues for data generation have significantly evolved, and therefore, large-scale and diverse types of data are being collected for downstream tasks. However, some automated tools can curate data with many vulnerabilities (e.g., missing values, wrong values, outliers, skewed...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10930894/ |
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