Together with impressive advances touching every aspect of our society, AI technology
based on Deep Neural Networks (DNN) is bringing increasing security concerns. While …

Although backdoor learning is an active research topic in the NLP domain, the literature
lacks studies that systematically categorize and summarize backdoor attacks and defenses …

Recent research shows deep neural networks are vulnerable to different types of attacks,
such as adversarial attacks, data poisoning attacks, and backdoor attacks. Among them …

Code models, such as CodeBERT and CodeT5, offer general-purpose representations of
code and play a vital role in supporting downstream automated software engineering tasks …

In the software engineering (SE) community, deep learning (DL) has recently been applied
to many source code processing tasks, achieving state-of-the-art results. Due to the poor …

Deep learning models have become key enablers of voice user interfaces. With the growing
trend of adopting outsourced training of these models, backdoor attacks, stealthy yet …

Deep neural networks (DNN) models have been widely applied in many tasks. However,
recent researches have shown that DNN models are vulnerable to backdoor attacks. A …

Reinforcement learning (RL) makes an agent learn from trial-and-error experiences
gathered during the interaction with the environment. Recently, offline RL has become a …

Backdoor attacks are commonly executed by contaminating training data, such that a trigger
can activate predetermined harmful effects during the test phase. In this work, we present …

In the software engineering community, deep learning (DL) has recently been applied to
many source code processing tasks. Due to the poor interpretability of DL models, their …