The success of machine learning is fueled by the increasing availability of computing power
and large training datasets. The training data is used to learn new models or update existing …

Backdoor attack intends to inject hidden backdoor into the deep neural networks (DNNs),
such that the prediction of the infected model will be maliciously changed if the hidden …

Backdoor injection attack is an emerging threat to the security of neural networks, however,
there still exist limited effective defense methods against the attack. In this paper, we …

Recent research has confirmed the feasibility of backdoor attacks in deep reinforcement
learning (RL) systems. However, the existing attacks require the ability to arbitrarily modify …

Although federated learning can provide privacy protection for individual raw data, some
studies have shown that the shared parameters or gradients under federated learning may …