Lingjuan Lyu
Lingjuan Lyu
Verified email at - Homepage
Cited by
Cited by
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
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
Deep learning aided grant-free NOMA toward reliable low-latency access in tactile Internet of Things
N Ye, X Li, H Yu, A Wang, W Liu, X Hou
IEEE Transactions on Industrial Informatics 15 (5), 2995-3005, 2019
Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices
YL Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan, Dusit Niyato, Zengxiang Li ...
IEEE Internet of Things Journal, 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
Threats to federated learning: A survey
L Lyu, H Yu, Q Yang
arXiv preprint arXiv:2003.02133, 2020
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
Privacy-preserving collaborative fuzzy clustering
L Lyu, JC Bezdek, YW Law, X He, M Palaniswami
Data & Knowledge Engineering 116, 21-41, 2018
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
Privacy-preserving aggregation of smart metering via transformation and encryption
L Lyu, YW Law, J Jin, M Palaniswami
2017 IEEE Trustcom/BigDataSE/ICESS, 472-479, 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
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
arXiv preprint arXiv:2004.08856, 2020
Privacy-preserving machine learning and data aggregation for Internet of Things
L Lyu
吴康, 吕灵娟, 杨胜利, 孙锐
网络安全技术与应用, 46-49, 2011
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
FORESEEN: Towards differentially private deep inference for intelligent Internet of Things
L Lyu, JC Bezdek, J Jin, Y Yang
IEEE Journal on Selected Areas in Communications 38 (10), 2418-2429, 2020
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
Towards Distributed Privacy-Preserving Prediction
L Lyu, YW Law, KS Ng, S Xue, J Zhao, M Yang, L Liu
arXiv preprint arXiv:1910.11478, 2019
The system can't perform the operation now. Try again later.
Articles 1–20