Machine learning (ML) has gained widespread adoption in a variety of fields, including
computer vision and natural language processing. However, ML models are vulnerable to …

Membership inference (MI) attacks mainly aim to infer whether a data record was used to
train a target model or not. Due to the serious privacy risks, MI attacks have been attracting a …

Membership inference (MI) attacks threaten user privacy through determining if a given data
example has been used to train a target model. However, it has been increasingly …

摘要机器学习被广泛应用于各个领域, 已成为推动各行业革命的强大动力,
极大促进了人工智能的繁荣与发展. 同时, 机器学习模型的训练和预测均需要大量数据 …

Membership inference (MI) attacks threaten user privacy through determining if a given data
example has been used to train a target model. Existing MI defenses protect the …

Purpose. Machine learning (ML) has revolutionized data processing and analysis, with
applications in health showing great promise. However, ML poses privacy risks, as models …