Machine learning (ML) models are applied in an increasing variety of domains. The
availability of large amounts of data and computational resources encourages the …

Due to the greatly improved capabilities of devices, massive data, and increasing concern
about data privacy, Federated Learning (FL) has been increasingly considered for …

Backdoor attack intends to embed hidden backdoors into deep neural networks (DNNs), so
that the attacked models perform well on benign samples, whereas their predictions will be …

Deep Neural Network (DNN) watermarking is a method for provenance verification of DNN
models. Watermarking should be robust against watermark removal attacks that derive a …

Watermarking is a commonly used strategy to protect creators' rights to digital images,
videos and audio. Recently, watermarking methods have been extended to deep learning …

Watermarking of deep neural networks (DNN) can enable their tracing once released by a
data owner to an online platform. In this paper, we generalize white-box watermarking …

Copyright protection for deep neural networks (DNNs) is an urgent need for AI corporations.
To trace illegally distributed model copies, DNN watermarking is an emerging technique for …

The training and creation of deep learning model is usually costly, thus the trained model
can be regarded as an intellectual property (IP) of the model creator. However, malicious …

Deep Neural Networks (DNNs), from AlexNet to ResNet to ChatGPT, have made
revolutionary progress in recent years, and are widely used in various fields. The high …

The knowledge of a deep learning model may be transferred to a student model, leading to
intellectual property infringement or vulnerability propagation. Detecting such knowledge …