On the Lift, Related Privacy Measures, and Applications to Privacy–Utility Trade-Offs
This paper investigates lift, the likelihood ratio between the posterior and prior belief about sensitive features in a dataset. Maximum and minimum lifts over sensitive features quantify the adversary’s knowledge gain and should be bounded to protect privacy. We demonstrate that max- and min-lifts...
Сохранить в:
| Главные авторы: | , , |
|---|---|
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI AG
2023-04-01
|
| Серии: | Entropy |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/1099-4300/25/4/679 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
|