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 …

The risk posed by Membership Inference Attack (MIA) to deep learning models for Computer
Vision (CV) tasks is well known, but MIA has not been addressed or explored fully in the …

Machine learning (ML) is vulnerable to inference (eg, membership inference, property
inference, and data reconstruction) attacks that aim to infer the private information of training …

Abstract Machine Learning as a Service (MLaaS) has significantly advanced data-driven
decision-making and the development of intelligent applications. However, the privacy risks …

Abstract Machine learning (ML) is vulnerable to inference (eg, membership inference,
property inference, and data reconstruction) attacks that aim to infer the private information …

Machine learning models are vulnerable to both security attacks (eg, adversarial examples)
and privacy attacks (eg, private attribute inference). We take the first step to mitigate both the …

Machine learning systems are becoming widely adopted and ubiquitous. Not only are there
a growth of products in which machine learning is at their core like autonomous vehicles, but …