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Curriculum Learning and Pattern-Aware Highly Efficient Privacy-Preserving Scheme for Mixed Data Outsourcing with Minimal Utility Loss

A complex problem when outsourcing personal data for public use is balancing privacy protection with utility, and anonymization is a viable solution to address this issue. However, conventional anonymization methods often overlook global information regarding the composition of attributes in data, l...

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Principais autores: Abdul Majeed, Kyunghyun Lee, Seong Oun Hwang
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2025-11-01
coleção:Applied Sciences
Assuntos:
anonymization
curriculum learning
differential privacy
<i>k</i>-anonymity
diversity
data outsourcing
Acesso em linha:https://www.mdpi.com/2076-3417/15/21/11849
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