Malicious utilization of a query interface can compromise the confidentiality of ML-as-a-
Service (MLaaS) systems via model extraction attacks. Previous studies have proposed to …

The equation-solving model extraction attack is an intuitively simple but devastating attack to
steal confidential information of regression models through a sufficient number of queries …

In secure machine learning inference, most of the schemes assume that the server is semi-
honest (honestly following the protocol but attempting to infer additional information) …

The emergence of new machine learning methods has led to their widespread application
across various domains, significantly advancing the field of artificial intelligence. However …

Network intrusion detection systems (IDS) are often considered effective to thwart cyber
attacks. Currently, state-of-the-art (SOTA) IDSs are mainly based on machine learning (ML) …

In the recent two decades, we have witnessed the dramatic development of artificial
intelligence (AI in short), not only in artificial intelligence itself but also its applications in …

In the Big Data era, the wide usage of mobile devices has led to large amounts of
information release and sharing through social networks, where sensitive information of the …

The cyber–physical infrastructure of a smart grid requires data-dependent artificial
intelligence (AI)-based forecasting schemes for predicting different aspects for the short-to …

In recent years, deep learning (DL) models have attracted widespread concern. Due to its
own characteristics, DL has been successfully applied in the fields of object detection …

Between the changing Industry 4.0 landscape and the rise of Industry 5.0, where human
intelligence and intelligent machines work together, vast amounts of privacy-sensitive data …