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发表时间：2024-11-19

发表刊物：Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

卷号：573 LNICST

页面范围：320-332

ISSN号：1867-8211

关键字：Adversarial machine learning; Breakings; Contrastive Learning; Data informations; Differential privacies; Information leakage; Machine learning models; Modeling parameters; Personalized federated learning; Privacy protection; Self-supervised learning; Training data; User data; User terminals