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Di Wu
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Recent advances in video-based human action recognition using deep learning: A review
D Wu, N Sharma, M Blumenstein
2017 International Joint Conference on Neural Networks (IJCNN), 2865-2872, 2017
1172017
A survey on latest botnet attack and defense
L Zhang, S Yu, D Wu, P Watters
2011IEEE 10th International Conference on Trust, Security and Privacy in …, 2011
972011
Poisoning attack in federated learning using generative adversarial nets
J Zhang, J Chen, D Wu, B Chen, S Yu
2019 18th IEEE International Conference On Trust, Security And Privacy In …, 2019
732019
Multi-task network anomaly detection using federated learning
Y Zhao, J Chen, D Wu, J Teng, S Yu
Proceedings of the tenth international symposium on information and …, 2019
552019
Robust feature-based automated multi-view human action recognition system
KP Chou, M Prasad, D Wu, N Sharma, DL Li, YF Lin, M Blumenstein, ...
IEEE Access 6, 15283-15296, 2018
502018
Pdgan: A novel poisoning defense method in federated learning using generative adversarial network
Y Zhao, J Chen, J Zhang, D Wu, J Teng, S Yu
International Conference on Algorithms and Architectures for Parallel …, 2019
312019
On addressing the imbalance problem: a correlated KNN approach for network traffic classification
D Wu, X Chen, C Chen, J Zhang, Y Xiang, W Zhou
International Conference on Network and System Security, 138-151, 2015
142015
From distributed machine learning to federated learning: In the view of data privacy and security
S Shen, T Zhu, D Wu, W Wang, W Zhou
Concurrency and Computation: Practice and Experience 34 (16), e6002, 2022
132022
Detecting and mitigating poisoning attacks in federated learning using generative adversarial networks
Y Zhao, J Chen, J Zhang, D Wu, M Blumenstein, S Yu
Concurrency and Computation: Practice and Experience 34 (7), e5906, 2022
102022
Adversarial action data augmentation for similar gesture action recognition
D Wu, J Chen, N Sharma, S Pan, G Long, M Blumenstein
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
82019
Fooling intrusion detection systems using adversarially autoencoder
J Chen, D Wu, Y Zhao, N Sharma, M Blumenstein, S Yu
Digital Communications and Networks 7 (3), 453-460, 2021
72021
Defending poisoning attacks in federated learning via adversarial training method
J Zhang, D Wu, C Liu, B Chen
International Conference on Frontiers in Cyber Security, 83-94, 2020
52020
Network anomaly detection using federated learning and transfer learning
Y Zhao, J Chen, Q Guo, J Teng, D Wu
International Conference on Security and Privacy in Digital Economy, 219-231, 2020
42020
Feature-dependent graph convolutional autoencoders with adversarial training methods
D Wu, R Hu, Y Zheng, J Jiang, N Sharma, M Blumenstein
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
42019
A privacy-preserving access control scheme with verifiable and outsourcing capabilities in fog-cloud computing
Z Cheng, J Zhang, H Qian, M Xiang, D Wu
International Conference on Algorithms and Architectures for Parallel …, 2019
12019
Network anomaly detection by using a time-decay closed frequent pattern
Y Zhao, J Chen, D Wu, J Teng, N Sharma, A Sajjanhar, M Blumenstein
Information 10 (8), 262, 2019
12019
Detecting stepping stones by abnormal causality probability
S Wen, D Wu, P Li, Y Xiang, W Zhou, G Wei
Security and Communication Networks 8 (10), 1831-1844, 2015
12015
VPFL: A verifiable privacy-preserving federated learning scheme for edge computing systems
J Zhang, Y Liu, D Wu, S Lou, B Chen, S Yu
Digital Communications and Networks, 2022
2022
Defending against Membership Inference Attacks in Federated learning via Adversarial Example
Y Xie, B Chen, J Zhang, D Wu
2021 17th International Conference on Mobility, Sensing and Networking (MSN …, 2021
2021
Student Sentiment Analysis Through Students’ Assignments
D Wu, N Sharma, J Zhang, J Chen, M Prasad, M Blumenstein
2019 International Joint Conferences on Artificial Intelligence (Workshop), 2019
2019
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