Lingjuan Lyu
Lingjuan Lyu
Sony AI
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PPFA: Privacy preserving fog-enabled aggregation in smart grid
L Lyu, K Nandakumar, B Rubinstein, J Jin, J Bedo, M Palaniswami
IEEE Transactions on Industrial Informatics 14 (8), 3733-3744, 2018
Privacy-preserving blockchain-based federated learning for IoT devices
Y Zhao, J Zhao, L Jiang, R Tan, D Niyato, Z Li, L Lyu, Y Liu
IEEE Internet of Things Journal 8 (3), 1817-1829, 2020
Threats to federated learning: A survey
L Lyu, H Yu, Q Yang
FL-IJCAI’20, 2020
Fog-empowered anomaly detection in IoT using hyperellipsoidal clustering
L Lyu, J Jin, S Rajasegarar, X He, M Palaniswami
IEEE Internet of Things Journal 4 (5), 1174-1184, 2017
Towards fair and privacy-preserving federated deep models
L Lyu, J Yu, K Nandakumar, Y Li, X Ma, J Jin, H Yu, KS Ng
IEEE Transactions on Parallel and Distributed Systems 31 (11), 2524-2541, 2020
Fog-embedded deep learning for the Internet of Things
L Lyu, JC Bezdek, X He, J Jin
IEEE Transactions on Industrial Informatics 15 (7), 4206-4215, 2019
Local differential privacy-based federated learning for internet of things
Y Zhao, J Zhao, M Yang, T Wang, N Wang, L Lyu, D Niyato, KY Lam
IEEE Internet of Things Journal 8 (11), 8836-8853, 2020
Privacy-preserving collaborative deep learning with application to human activity recognition
L Lyu, X He, YW Law, M Palaniswami
Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017
Local differential privacy and its applications: A comprehensive survey
M Yang, L Lyu, J Zhao, T Zhu, KY Lam
arXiv preprint arXiv:2008.03686, 2020
Privacy and robustness in federated learning: Attacks and defenses
L Lyu, H Yu, X Ma, L Sun, J Zhao, Q Yang, PS Yu
arXiv preprint arXiv:2012.06337, 2020
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification
J Zhou, C Chen, L Zheng, H Wu, J Wu, X Zheng, B Wu, Z Liu, L Wang
arXiv preprint arXiv:2005.11903, 2020
Data poisoning attacks on federated machine learning
G Sun, Y Cong, J Dong, Q Wang, J Liu
arXiv preprint arXiv:2004.10020, 2020
Privacy-preserving collaborative fuzzy clustering
L Lyu, JC Bezdek, YW Law, X He, M Palaniswami
Data & Knowledge Engineering 116, 21-41, 2018
Federated model distillation with noise-free differential privacy
L Sun, L Lyu
IJCAI’21, 2020
Towards differentially private text representations
L Lyu, Y Li, X He, T Xiao
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
Fedgnn: Federated graph neural network for privacy-preserving recommendation
C Wu, F Wu, Y Cao, Y Huang, X Xie
FL-ICML’21 Oral, 2021
Differentially private knowledge distillation for mobile analytics
L Lyu, CH Chen
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
An improved scheme for privacy-preserving collaborative anomaly detection
L Lyu, YW Law, SM Erfani, C Leckie, M Palaniswami
2016 IEEE International Conference on Pervasive Computing and Communication …, 2016
Neural attention distillation: Erasing backdoor triggers from deep neural networks
Y Li, X Lyu, N Koren, L Lyu, B Li, X Ma
ICLR’21, 2021
How to democratise and protect AI: fair and differentially private decentralised deep learning
L Lyu, Y Li, K Nandakumar, J Yu, X Ma
IEEE Transactions on Dependable and Secure Computing, 2020
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