Machine learning (ML) models have been widely applied to various applications, including
image classification, text generation, audio recognition, and graph data analysis. However …

As machine learning becomes more widely used, the need to study its implications in
security and privacy becomes more urgent. Although the body of work in privacy has been …

Machine learning (ML) has become a core component of many real-world applications and
training data is a key factor that drives current progress. This huge success has led Internet …

Machine learning (ML) has been widely adopted in various privacy-critical applications, eg,
face recognition and medical image analysis. However, recent research has shown that ML …

In a membership inference attack, an attacker aims to infer whether a data sample is in a
target classifier's training dataset or not. Specifically, given a black-box access to the target …

Deep learning has achieved overwhelming success, spanning from discriminative models to
generative models. In particular, deep generative models have facilitated a new level of …

Conventional attacks of insider employees and emerging APT are both major threats for the
organizational information system. Existing detections mainly concentrate on users' behavior …

The right to be forgotten states that a data owner has the right to erase their data from an
entity storing it. In the context of machine learning (ML), the right to be forgotten requires an …

Machine learning (ML) has progressed rapidly during the past decade and the major factor
that drives such development is the unprecedented large-scale data. As data generation is a …

Graph is an important data representation ubiquitously existing in the real world. However,
analyzing the graph data is computationally difficult due to its non-Euclidean nature. Graph …