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Wenjuan Li
Wenjuan Li
The Education University of Hong Kong
Verified email at cityu.edu.hk - Homepage
Title
Cited by
Cited by
Year
A survey on OpenFlow-based Software Defined Networks: Security challenges and countermeasures
W Li, W Meng, LF Kwok
Journal of Network and Computer Applications 68, 126-139, 2016
2132016
Designing collaborative blockchained signature-based intrusion detection in IoT environments
W Li, S Tug, W Meng, Y Wang
Future Generation Computer Systems 96, 481-489, 2019
1822019
Enhancing medical smartphone networks via blockchain-based trust management against insider attacks
W Meng, W Li, L Zhu
IEEE Transactions on Engineering Management 67 (4), 1377-1386, 2019
1212019
Enhancing collaborative intrusion detection via disagreement-based semi-supervised learning in IoT environments
W Li, W Meng, MH Au
Journal of Network and Computer Applications 161, 102631, 2020
1142020
EFM: enhancing the performance of signature-based network intrusion detection systems using enhanced filter mechanism
W Meng, W Li, LF Kwok
computers & security 43, 189-204, 2014
1062014
A blockchain-empowered AAA scheme in the large-scale HetNet
N Shi, L Tan, W Li, X Qi, K Yu
Digital Communications and Networks 7 (3), 308-316, 2021
1002021
Enhancing trust management for wireless intrusion detection via traffic sampling in the era of big data
W Meng, W Li, C Su, J Zhou, R Lu
Ieee Access 6, 7234-7243, 2017
992017
Blockchain-based trust management in cloud computing systems: a taxonomy, review and future directions
W Li, J Wu, J Cao, N Chen, Q Zhang, R Buyya
Journal of Cloud Computing 10 (1), 35, 2021
942021
Enhancing collaborative intrusion detection networks against insider attacks using supervised intrusion sensitivity-based trust management model
W Li, W Meng, LF Kwok, HS Horace
Journal of Network and Computer Applications 77, 135-145, 2017
892017
Design of intelligent KNN‐based alarm filter using knowledge‐based alert verification in intrusion detection
W Meng, W Li, LF Kwok
Security and Communication Networks 8 (18), 3883-3895, 2015
862015
Adaptive machine learning‐based alarm reduction via edge computing for distributed intrusion detection systems
Y Wang, W Meng, W Li, Z Liu, Y Liu, H Xue
Concurrency and Computation: Practice and Experience 31 (19), e5101, 2019
802019
A bayesian inference-based detection mechanism to defend medical smartphone networks against insider attacks
W Meng, W Li, Y Xiang, KKR Choo
Journal of Network and Computer Applications 78, 162-169, 2017
772017
A fog-based privacy-preserving approach for distributed signature-based intrusion detection
Y Wang, W Meng, W Li, J Li, WX Liu, Y Xiang
Journal of Parallel and Distributed Computing 122, 26-35, 2018
762018
Detecting insider attacks in medical cyber–physical networks based on behavioral profiling
W Meng, W Li, Y Wang, MH Au
Future Generation Computer Systems 108, 1258-1266, 2020
692020
An improved particle swarm optimization algorithm suitable for photovoltaic power tracking under partial shading conditions
K Hu, S Cao, W Li, F Zhu
IEEE Access 7, 143217-143232, 2019
652019
Enhancing the security of blockchain-based software defined networking through trust-based traffic fusion and filtration
W Meng, W Li, J Zhou
Information Fusion 70, 60-71, 2021
582021
Design of Intrusion Sensitivity-Based Trust Management Model for Collaborative Intrusion Detection Networks
W Li, W Meng, LF Kwok
The 8th IFIP WG 11.11 International Conference on Trust Management (IFIPTM …, 2014
582014
Enhancing trust evaluation using intrusion sensitivity in collaborative intrusion detection networks: feasibility and challenges
W Li, Y Meng, LF Kwok
2013 ninth international conference on computational intelligence and …, 2013
572013
Design of multi-view based email classification for IoT systems via semi-supervised learning
W Li, W Meng, Z Tan, Y Xiang
Journal of Network and Computer Applications 128, 56-63, 2019
562019
Towards blockchain-based software-defined networking: security challenges and solutions
W Li, W Meng, Z Liu, MH Au
IEICE Transactions on Information and Systems 103 (2), 196-203, 2020
542020
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