Di Wu

According to our database, Di Wu authored at least 47 papers between 2004 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

A Comprehensive Survey on Machine Learning Driven Material Defect Detection.

Jun Bai, Di Wu, Tristan Shelley, Peter Schubel, David Twine, John Russell, Xuesen Zeng, Ji Zhang

ACM Comput. Surv., November, 2025

Deep learning model inversion attacks and defenses: a comprehensive survey.

Wencheng Yang, Song Wang, Di Wu, Taotao Cai, Yanming Zhu, Shicheng Wei, Yi-Ying Zhang, Xu Yang, Zhaohui Tang, Yan Li

Artif. Intell. Rev., August, 2025

FedMLC: White-Box Model Watermarking for Copyright Protection in Federated Learning for IoT Environment.

Weitong Chen, Wei Zhang, Di Wu, Anja Keskinarkaus, Tapio Seppänen, Jiale Zhang, Longxiang Gao, Tom H. Luan

IEEE Internet Things J., July, 2025

Who Owns This Sample: Cross-Client Membership Inference Attack in Federated Graph Neural Networks.

Kunhao Li, Di Wu, Jun Bai, Jing Xu, Lei Yang, Ziyi Zhang, Yiliao Song, Wencheng Yang, Taotao Cai, Yan Li

CoRR, July, 2025

FedMLAC: Mutual Learning Driven Heterogeneous Federated Audio Classification.

Jun Bai, Rajib Rana, Di Wu, Youyang Qu, Xiaohui Tao, Ji Zhang

CoRR, June, 2025

Non-IID Free Federated Learning With Fuzzy Optimization for Consumer Electronics Systems.

Jun Bai, Di Wu, Shan Zeng, Yao Zhao, Youyang Qu, Shui Yu

IEEE Trans. Consumer Electron., May, 2025

Privacy Inference Attack and Defense in Centralized and Federated Learning: A Comprehensive Survey.

Bosen Rao, Jiale Zhang, Di Wu, Chengcheng Zhu, Xiaobing Sun, Bing Chen

IEEE Trans. Artif. Intell., February, 2025

Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey.

Wencheng Yang, Song Wang, Di Wu, Taotao Cai, Yanming Zhu, Shicheng Wei, Yiying Zhang, Xu Yang, Yan Li

CoRR, January, 2025

Refining Water Body Extraction by Remote Sensing With Deep Learning Models: Exploring Different Band Combinations.

Ziheng Feng, Fei Zhang, Xu Ma, Chi-Yung Jim, Di Wu, Dong Liu, Saheed Adeyinka Oke, Weiwei Wang, Lifei Wei, Songlin Nie, Zhihui Li, Haowei Xu

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025

SFFL: Self-aware fairness federated learning framework for heterogeneous data distributions.

Jiale Zhang, Ye Li, Di Wu, Yanchao Zhao, Shivakumara Palaiahnakote

Expert Syst. Appl., 2025

EPAD: Ethereum phishing scam detection via graph contrastive learning.

Hao Sui, Jiale Zhang, Bing Chen, Di Wu, Xiaobing Sun, Shivakumara Palaiahnakote

Expert Syst. Appl., 2025

Beyond Dataset Watermarking: Model-Level Copyright Protection for Code Summarization Models.

Jiale Zhang, Haoxuan Li, Di Wu, Xiaobing Sun, Qinghua Lu, Guodong Long

Proceedings of the ACM on Web Conference 2025, 2025

2024

From Wide to Deep: Dimension Lifting Network for Parameter-Efficient Knowledge Graph Embedding.

Borui Cai, Yong Xiang, Longxiang Gao, Di Wu, He Zhang, Jiong Jin, Tom H. Luan

IEEE Trans. Knowl. Data Eng., December, 2024

EXVul: Toward Effective and Explainable Vulnerability Detection for IoT Devices.

Sicong Cao, Xiaobing Sun, Wei Liu, Di Wu, Jiale Zhang, Yan Li, Tom H. Luan, Longxiang Gao

IEEE Internet Things J., June, 2024

A Unified Solution to Diverse Heterogeneities in One-shot Federated Learning.

Jun Bai, Yiliao Song, Di Wu, Atul Sajjanhar, Yong Xiang, Wei Zhou, Xiaohui Tao, Yan Li

CoRR, 2024

DMGNN: Detecting and Mitigating Backdoor Attacks in Graph Neural Networks.

Hao Sui, Bing Chen, Jiale Zhang, Chengcheng Zhu, Di Wu, Qinghua Lu, Guodong Long

CoRR, 2024

A Comprehensive Survey on Machine Learning Driven Material Defect Detection: Challenges, Solutions, and Future Prospects.

Jun Bai, Di Wu, Tristan Shelley, Peter Schubel, David Twine, John Russell, Xuesen Zeng, Ji Zhang

CoRR, 2024

A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research.

Sicong Cao, Xiaobing Sun, Ratnadira Widyasari, David Lo, Xiaoxue Wu, Lili Bo, Jiale Zhang, Bin Li, Wei Liu, Di Wu, Yixin Chen

CoRR, 2024

BADFSS: Backdoor Attacks on Federated Self-Supervised Learning.

Jiale Zhang, Chengcheng Zhu, Di Wu, Xiaobing Sun, Jianming Yong, Guodong Long

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

FedInverse: Evaluating Privacy Leakage in Federated Learning.

Di Wu, Jun Bai, Yiliao Song, Junjun Chen, Wei Zhou, Yong Xiang, Atul Sajjanhar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

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

Jiale Zhang, Yue Liu, Di Wu, Shuai Lou, Bing Chen, Shui Yu

Digit. Commun. Networks, August, 2023

Hybrid KD-NFT: A multi-layered NFT assisted robust Knowledge Distillation framework for Internet of Things.

Nai Wang, Junjun Chen, Di Wu, Wencheng Yang, Yong Xiang, Atul Sajjanhar

J. Inf. Secur. Appl., June, 2023

2022

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

Ying Zhao, Junjun Chen, Jiale Zhang, Di Wu, Michael Blumenstein, Shui Yu

Concurr. Comput. Pract. Exp., 2022

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

Sheng Shen, Tianqing Zhu, Di Wu, Wei Wang, Wanlei Zhou

Concurr. Comput. Pract. Exp., 2022

A Blockchain-based Multi-layer Decentralized Framework for Robust Federated Learning.

Di Wu, Nai Wang, Jiale Zhang, Yuan Zhang, Yong Xiang, Longxiang Gao

Proceedings of the International Joint Conference on Neural Networks, 2022

Campus Network Intrusion Detection based on Federated Learning.

Junjun Chen, Qiang Guo, Zhongnan Fu, Qun Shang, Hao Ma, Di Wu

Proceedings of the International Joint Conference on Neural Networks, 2022

2021

Fooling intrusion detection systems using adversarially autoencoder.

Junjun Chen, Di Wu, Ying Zhao, Nabin Sharma, Michael Blumenstein, Shui Yu

Digit. Commun. Networks, 2021

Defending against Membership Inference Attacks in Federated learning via Adversarial Example.

Yuanyuan Xie, Bing Chen, Jiale Zhang, Di Wu

Proceedings of the 17th International Conference on Mobility, Sensing and Networking, 2021

2020

Network Anomaly Detection Using Federated Learning and Transfer Learning.

Ying Zhao, Junjun Chen, Qianling Guo, Jian Teng, Di Wu

Proceedings of the Security and Privacy in Digital Economy, 2020

Defending Poisoning Attacks in Federated Learning via Adversarial Training Method.

Jiale Zhang, Di Wu, Chengyong Liu, Bing Chen

Proceedings of the Frontiers in Cyber Security - Third International Conference, 2020

2019

Video-based similar gesture action recognition using deep learning and GAN-based approaches

Di Wu

PhD thesis, 2019

Network Anomaly Detection by Using a Time-Decay Closed Frequent Pattern.

Ying Zhao, Junjun Chen, Di Wu, Jian Teng, Nabin Sharma, Atul Sajjanhar, Michael Blumenstein

Inf., 2019

Poisoning Attack in Federated Learning using Generative Adversarial Nets.

Jiale Zhang, Junjun Chen, Di Wu, Bing Chen, Shui Yu

Proceedings of the 18th IEEE International Conference On Trust, 2019

Multi-Task Network Anomaly Detection using Federated Learning.

Ying Zhao, Junjun Chen, Di Wu, Jian Teng, Shui Yu

Proceedings of the Tenth International Symposium on Information and Communication Technology, 2019

Feature-Dependent Graph Convolutional Autoencoders with Adversarial Training Methods.

Di Wu, Ruiqi Hu, Yu Zheng, Jing Jiang, Nabin Sharma, Michael Blumenstein

Proceedings of the International Joint Conference on Neural Networks, 2019

Adversarial Action Data Augmentation for Similar Gesture Action Recognition.

Di Wu, Junjun Chen, Nabin Sharma, Shirui Pan, Guodong Long, Michael Blumenstein

Proceedings of the International Joint Conference on Neural Networks, 2019

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

Ying Zhao, Junjun Chen, Jiale Zhang, Di Wu, Jian Teng, Shui Yu

Proceedings of the Algorithms and Architectures for Parallel Processing, 2019

A Privacy-Preserving Access Control Scheme with Verifiable and Outsourcing Capabilities in Fog-Cloud Computing.

Zhen Cheng, Jiale Zhang, Hongyan Qian, Mingrong Xiang, Di Wu

Proceedings of the Algorithms and Architectures for Parallel Processing, 2019

2018

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

Kuang-Pen Chou, Mukesh Prasad, Di Wu, Nabin Sharma, Dong-Lin Li, Yu-Feng Lin, Michael Blumenstein, Wen-Chieh Lin, Chin-Teng Lin

IEEE Access, 2018

An End-to-End Hierarchical Classification Approach for Similar Gesture Recognition.

Di Wu, Nabin Sharma, Michael Blumenstein

Proceedings of the 2018 International Conference on Image and Vision Computing New Zealand, 2018

Similar Gesture Recognition using Hierarchical Classification Approach in RGB Videos.

Di Wu, Nabin Sharma, Michael Blumenstein

Proceedings of the 2018 Digital Image Computing: Techniques and Applications, 2018

2017

Recent advances in video-based human action recognition using deep learning: A review.

Di Wu, Nabin Sharma, Michael Blumenstein

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2015

Detecting stepping stones by abnormal causality probability.

Sheng Wen, Di Wu, Ping Li, Yang Xiang, Wanlei Zhou, Guiyi Wei

Secur. Commun. Networks, 2015

2014

On Addressing the Imbalance Problem: A Correlated KNN Approach for Network Traffic Classification.

Di Wu, Xiao Chen, Chao Chen, Jun Zhang, Yang Xiang, Wanlei Zhou

Proceedings of the Network and System Security - 8th International Conference, 2014

2013

Detecting Stepping Stones by Abnormal Causality Probability.

Sheng Wen, Ping Li, Di Wu, Yang Xiang, Wanlei Zhou

Proceedings of the Cyberspace Safety and Security - 5th International Symposium, 2013

2011

A Survey on Latest Botnet Attack and Defense.

Lei Zhang, Shui Yu, Di Wu, Paul A. Watters

Proceedings of the IEEE 10th International Conference on Trust, 2011

2004

Statistical Issues with Labeled Sample Size Analysis for Semi-Supervised Linear Discriminant Analysis.

Han Liu, Di Wu, Ji Zhang, Xiaolin Yang, Xiaobin Yuan, Rafal Kustra

Proceedings of the International Conference on Artificial Intelligence, 2004