Dynamic Optimization Method for Differential Privacy Parameters Based on Data Sensitivity in Federated Learning
This paper introduces a dynamic optimization framework for differential privacy parameters in federated learning systems that adapts privacy budgets based on real-time data sensitivity assessment. The proposed methodology employs a lightweight sensitivity analyzer that categorizes data samples into...
Gorde:
| Egile Nagusiak: | , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Scientific Publication Center
2025-06-01
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| Saila: | Journal of Advanced Computing Systems |
| Gaiak: | |
| Sarrera elektronikoa: | https://scipublication.com/index.php/JACS/article/view/214 |
| Etiketak: |
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