Local Distortion Hiding Algorithm in Medical Data: A Case Study sing CART.
Data sharing has become an increasingly common process among health organizations, but any organization will most likely try to hide some sensitive patterns before sharing its data with others. Local Distortion Hiding (LDH), a recently proposed algorithm, has been evaluated only on the assumption of...
| Publicado en: | Studies in Health Technology & Informatics Vol. 272; pp. 99 - 103 |
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| Autores principales: | , , |
| Formato: | tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Data sharing has become an increasingly common process among health organizations, but any organization will most likely try to hide some sensitive patterns before sharing its data with others. Local Distortion Hiding (LDH), a recently proposed algorithm, has been evaluated only on the assumption of an opponent using the J48 (C4.5) classification algorithm. We now extend the basic approach, and we present a medical dataset hiding case study of a processed by LDH and attacked with the CART algorithm. |
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