Neural Code Completion Tools (NCCTs) have reshaped the field of software engineering,
which are built upon the language modeling technique and can accurately suggest …

Deep neural networks (DNNs) are vulnerable to adversarial attacks, which lead to incorrect
predictions. In black-box settings, transfer attacks can be conveniently used to generate …

With the great achievement of vision transformers (ViTs), transformer-based approaches
have become the new paradigm for solving various computer vision tasks. However, recent …

Various transfer attack methods have been proposed to evaluate the robustness of deep
neural networks (DNNs). Although manifesting remarkable performance in generating …

Imperceptibility is one of the crucial requirements for adversarial examples. Previous
adversarial attacks on 3D point cloud recognition suffer from noticeable outliers, resulting in …

Today, black-box machine learning models are often subject to extraction attacks that aim to
retrieve their internal information. Black-box model extraction attacks are typically conducted …