Hongsheng Hu
Hongsheng Hu
Data61, CSIRO
Verified email at - Homepage
Cited by
Cited by
Membership inference attacks on machine learning: A survey
H Hu, Z Salcic, L Sun, G Dobbie, PS Yu, X Zhang
ACM Computing Surveys (CSUR) 54 (11s), 1-37, 2022
Source inference attacks in federated learning
H Hu, Z Salcic, L Sun, G Dobbie, X Zhang
2021 IEEE International Conference on Data Mining (ICDM), 1102-1107, 2021
Sports match prediction model for training and exercise using attention-based LSTM network
Q Zhang, X Zhang, H Hu, C Li, Y Lin, R Ma
Digital Communications and Networks 8 (4), 508-515, 2022
Differentially private locality sensitive hashing based federated recommender system
H Hu, G Dobbie, Z Salcic, M Liu, J Zhang, L Lyu, X Zhang
Concurrency and Computation: Practice and Experience 35 (14), e6233, 2023
Membership Inference via Backdooring
H Hu, Z Salcic, G Dobbie, J Chen, L Sun, X Zhang
IJCAI-22, 2022
EAR: an enhanced adversarial regularization approach against membership inference attacks
H Hu, Z Salcic, G Dobbie, Y Chen, X Zhang
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
A locality sensitive hashing based approach for federated recommender system
H Hu, G Dobbie, Z Salcic, M Liu, J Zhang, X Zhang
2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet …, 2020
A Duty to Forget, a Right to be Assured? Exposing Vulnerabilities in Machine Unlearning Services
H Hu, S Wang, J Chang, H Zhong, R Sun, S Hao, H Zhu, M Xue
Network and Distributed System Security Symposium (NDSS) 2024, 2024
Clustering-based efficient privacy-preserving face recognition scheme without compromising accuracy
M Liu, H Hu, H Xiang, C Yang, L Lyu, X Zhang
ACM Transactions on Sensor Networks (TOSN) 17 (3), 1-27, 2021
Deepiforest: A deep anomaly detection framework with hashing based isolation forest
H Xiang, H Hu, X Zhang
2022 IEEE International Conference on Data Mining (ICDM), 1251-1256, 2022
Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning
H Hu, S Wang, T Dong, M Xue
IEEE Symposium on Security and Privacy (S&P) 2024, 2024
OptIForest: Optimal Isolation Forest for Anomaly Detection
H Xiang, X Zhang, H Hu, L Qi, W Dou, M Dras, A Beheshti, X Xu
IJCAI-23, 2023
Source Inference Attacks: Beyond Membership Inference Attacks in Federated Learning
H Hu, X Zhang, Z Salcic, L Sun, KKR Choo, G Dobbie
IEEE Transactions on Dependable and Secure Computing, 2023
Shadow-free Membership Inference Attacks: Recommender Systems Are More Vulnerable Than You Thought
X Chi, X Zhang, Y Wang, L Qi, A Beheshti, X Xu, KKR Choo, S Wang, ...
IJCAI-24, 2024
Cardinality Counting in" Alcatraz": A Privacy-aware Federated Learning Approach
N Wu, X Yuan, S Wang, H Hu, M Xue
Proceedings of the ACM on Web Conference 2024, 3076-3084, 2024
LACMUS: Latent Concept Masking for General Robustness Enhancement of DNNs
S Wang, H Hu, J Chang, BZH Zhao, M Xue
2024 IEEE Symposium on Security and Privacy (S&P), 260-260, 2024
Symmetric Self-Paced Learning for Domain Generalization
D Zhao, YS Koh, G Dobbie, H Hu, P Fournier-Viger
Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 16961 …, 2024
DNN-GP: Diagnosing and Mitigating Model’s Faults Using Latent Concepts
S Wang, H Hu, J Chang, BZH Zhao, QA Chen, M Xue
USENIX Security 24, 2024
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