Di Wu

Detecting and mitigating poisoning attacks in federated learning using generative adversarial networks

Michael Blumenstein, Di Wu, Shui Yu, 2020, Concurr. Comput. Pract. Exp..

Poisoning Attack in Federated Learning using Generative Adversarial Nets

Bing Chen, Di Wu, Shui Yu, 2019, 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE).

From distributed machine learning to federated learning: In the view of data privacy and security pdf

Tianqing Zhu, Di Wu, Wanlei Zhou, 2020, Concurr. Comput. Pract. Exp..

VPFL: A verifiable privacy-preserving federated learning scheme for edge computing systems

Yue Liu, Jiale Zhang, Di Wu, 2022, Digital Communications and Networks.

Fooling intrusion detection systems using adversarially autoencoder

Michael Blumenstein, Di Wu, Shui Yu, 2020, Digit. Commun. Networks.

Defending Poisoning Attacks in Federated Learning via Adversarial Training Method

Di Wu, Bing Chen, Jiale Zhang, 2020, FCS.

Adversarial Action Data Augmentation for Similar Gesture Action Recognition

Michael Blumenstein, Di Wu, Shirui Pan, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

PDGAN: A Novel Poisoning Defense Method in Federated Learning Using Generative Adversarial Network

Di Wu, Shui Yu, Ying Zhao, 2019, ICA3PP.

Robust Feature-Based Automated Multi-View Human Action Recognition System

Di Wu, Michael Blumenstein, Wen-Chieh Lin, 2023, IEEE Access.