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2020 – today
- 2024
[j36]Yixuan Wu
, Lin Yang, Long Zhang, Laisen Nie, Li Zheng:
Intrusion Detection for Unmanned Aerial Vehicles Security: A Tiny Machine Learning Model. IEEE Internet Things J. 11(12): 20970-20982 (2024)- [j35]Yixuan Wu, Laisen Nie, Xuanrui Xiong, Balqies Sadoun, Lin Yang, Zhaolong Ning:
Incremental Update Intrusion Detection for Industry 5.0 Security: A Graph Attention Network-Enabled Approach. IEEE Trans. Consumer Electron. 70(1): 2004-2017 (2024) - [j34]Laisen Nie, Xiaojie Wang, Qinglin Zhao, Zhigang Shang, Li Feng, Guojun Li:
Digital Twin for Transportation Big Data: A Reinforcement Learning-Based Network Traffic Prediction Approach. IEEE Trans. Intell. Transp. Syst. 25(1): 896-906 (2024) - [j33]Jihao Yang, Wen Jiang, Laisen Nie:
Hypernetworks-Based Hierarchical Federated Learning on Hybrid Non-IID Datasets for Digital Twin in Industrial IoT. IEEE Trans. Netw. Sci. Eng. 11(2): 1413-1423 (2024) - [c7]Jihao Yang, Xinyang Deng, Laisen Nie, Wen Jiang:
A Federated Learning Mechanism with Feature Drift for Feature Distribution Skew. FUSION 2024: 1-7 - 2023
- [j32]Yixuan Wu, Laisen Nie, Shupeng Wang, Zhaolong Ning, Shengtao Li:
Intelligent Intrusion Detection for Internet of Things Security: A Deep Convolutional Generative Adversarial Network-Enabled Approach. IEEE Internet Things J. 10(4): 3094-3106 (2023) - [j31]Qiang He, Wei Qiao, Ali Kashif Bashir, Yuliang Cai, Laisen Nie, Yasser D. Al-Otaibi, Keping Yu:
Rumors Suppression in Healthcare System: Opinion-Based Comprehensive Learning Particle Swarm Optimization. IEEE Trans. Comput. Soc. Syst. 10(4): 1780-1790 (2023) - 2022
- [j30]Jiannan Wei, Qinchuan Zhu, Qianmu Li, Laisen Nie, Zhangyi Shen, Kim-Kwang Raymond Choo, Keping Yu:
A Redactable Blockchain Framework for Secure Federated Learning in Industrial Internet of Things. IEEE Internet Things J. 9(18): 17901-17911 (2022) - [j29]Laisen Nie, Yixuan Wu, Xiaojie Wang, Lei Guo, Guoyin Wang, Xinbo Gao, Shengtao Li:
Intrusion Detection for Secure Social Internet of Things Based on Collaborative Edge Computing: A Generative Adversarial Network-Based Approach. IEEE Trans. Comput. Soc. Syst. 9(1): 134-145 (2022) - [j28]Dawei Wang, Yixin He, Keping Yu, Gautam Srivastava, Laisen Nie, Ruonan Zhang:
Delay-Sensitive Secure NOMA Transmission for Hierarchical HAP-LAP Medical-Care IoT Networks. IEEE Trans. Ind. Informatics 18(8): 5561-5572 (2022) - [j27]Handi Chen, Shupeng Wang, Guojun Li, Laisen Nie, Xiaojie Wang, Zhaolong Ning:
Distributed Orchestration of Service Function Chains for Edge Intelligence in the Industrial Internet of Things. IEEE Trans. Ind. Informatics 18(9): 6244-6254 (2022) - [j26]Shupeng Wang, Laisen Nie, Guojun Li, Yixuan Wu, Zhaolong Ning:
A Multitask Learning-Based Network Traffic Prediction Approach for SDN-Enabled Industrial Internet of Things. IEEE Trans. Ind. Informatics 18(11): 7475-7483 (2022) - [j25]Yixin He, Laisen Nie, Tan Guo, Kuljeet Kaur, Mohammad Mehedi Hassan, Keping Yu:
A NOMA-Enabled Framework for Relay Deployment and Network Optimization in Double-Layer Airborne Access VANETs. IEEE Trans. Intell. Transp. Syst. 23(11): 22452-22466 (2022) - [j24]Xiaojie Wang, Laisen Nie, Zhaolong Ning, Lei Guo, Guoyin Wang, Xinbo Gao, Neeraj Kumar:
Deep Learning-Based Network Traffic Prediction for Secure Backbone Networks in Internet of Vehicles. ACM Trans. Internet Techn. 22(4): 87:1-87:20 (2022) - [c6]Jian Song, Hua Liu, Laisen Nie, Zhaolong Ning, Mohammad S. Obaidat, Balqies Sadoun:
Network Traffic Prediction for Intelligent Transportation Systems: A Reinforcement Learning Approach. GLOBECOM 2022: 245-250 - 2021
- [j23]Laisen Nie, Xiaojie Wang, Wentao Sun, Yongkang Li, Shengtao Li, Peng Zhang:
Imitation-Learning-Enabled Vehicular Edge Computing: Toward Online Task Scheduling. IEEE Netw. 35(3): 102-108 (2021) - [j22]Yongkang Li, Tong Wang, Tianyu Huo, Laisen Nie:
A Study on the Range Equation Modeling for Multichannel Medium-Earth-Orbit SAR-GMTI Systems. Remote. Sens. 13(14): 2734 (2021) - [j21]Laisen Nie, Wentao Sun, Shupeng Wang, Zhaolong Ning, Joel J. P. C. Rodrigues, Yixuan Wu, Shengtao Li:
Intrusion Detection in Green Internet of Things: A Deep Deterministic Policy Gradient-Based Algorithm. IEEE Trans. Green Commun. Netw. 5(2): 778-788 (2021) - [j20]Laisen Nie, Zhaolong Ning, Mohammad S. Obaidat, Balqies Sadoun, Huizhi Wang, Shengtao Li, Lei Guo, Guoyin Wang:
A Reinforcement Learning-Based Network Traffic Prediction Mechanism in Intelligent Internet of Things. IEEE Trans. Ind. Informatics 17(3): 2169-2180 (2021) - [j19]Ying Gao, Yijian Chen, Xiping Hu, Hongliang Lin, Yangliang Liu, Laisen Nie:
Blockchain Based IIoT Data Sharing Framework for SDN-Enabled Pervasive Edge Computing. IEEE Trans. Ind. Informatics 17(7): 5041-5049 (2021) - [j18]Laisen Nie, Xiaojie Wang, Shupeng Wang, Zhaolong Ning, Mohammad S. Obaidat, Balqies Sadoun, Shengtao Li:
Network Traffic Prediction in Industrial Internet of Things Backbone Networks: A Multitask Learning Mechanism. IEEE Trans. Ind. Informatics 17(10): 7123-7132 (2021) - 2020
- [j17]Laisen Nie, Huizhi Wang, Xin Jiang, Yi Guo, Shengtao Li:
Traffic Measurement Optimization Based on Reinforcement Learning in Large-Scale ITS-Oriented Backbone Networks. IEEE Access 8: 36988-36996 (2020) - [j16]Laisen Nie, Zhaolong Ning, Xiaojie Wang, Xiping Hu, Jun Cheng, Yongkang Li:
Data-Driven Intrusion Detection for Intelligent Internet of Vehicles: A Deep Convolutional Neural Network-Based Method. IEEE Trans. Netw. Sci. Eng. 7(4): 2219-2230 (2020)
2010 – 2019
- 2019
- [j15]Yongkang Li, Baochang Liu, Lei Wang, Hongmeng Chen, Laisen Nie, Lina Zeng, Guoan Bi:
An Accurate Imaging and Doppler Chirp Rate Estimation Algorithm for Airborne CSSAR-GMTI Systems. IEEE Access 7: 170077-170086 (2019) - [j14]Laisen Nie, Yixuan Wu, Huizhi Wang, Yongkang Li:
Anomaly Detection Based on Spatio-Temporal and Sparse Features of Network Traffic in VANETs. IEEE Access 7: 177954-177964 (2019) - [j13]Yongkang Li, Yongliang Wang, Baochang Liu, Shuang-xi Zhang, Laisen Nie, Guoan Bi:
A New Motion Parameter Estimation and Relocation Scheme for Airborne Three-Channel CSSAR-GMTI Systems. IEEE Trans. Geosci. Remote. Sens. 57(6): 4107-4120 (2019) - [c5]Laisen Nie, Huizhi Wang, Shimin Gong, Zhaolong Ning, Mohammad S. Obaidat, Kuei-Fang Hsiao:
Anomaly Detection Based on Spatio-Temporal and Sparse Features of Network Traffic in VANETs. GLOBECOM 2019: 1-6 - [c4]Huizhi Wang, Laisen Nie, Zhaolong Ning, Mohammad S. Obaidat, Runze Shang:
Traffic Measurement Optimization Based on Reinforcement Learning in Large-Scale IP Backbone Networks. GLOBECOM 2019: 1-6 - [c3]Yongkang Li, Laisen Nie:
A New Ground Moving Target Imaging Algorithm for High-Resolution Airborne CSSAR-GMTI Systems. IGARSS 2019: 2308-2311 - 2018
- [j12]Laisen Nie, Yongkang Li, Xiangjie Kong:
Spatio-Temporal Network Traffic Estimation and Anomaly Detection Based on Convolutional Neural Network in Vehicular Ad-Hoc Networks. IEEE Access 6: 40168-40176 (2018) - [j11]Laisen Nie, Xiaojie Wang, Liangtian Wan, Shui Yu, Houbing Song, Dingde Jiang:
Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks. Wirel. Commun. Mob. Comput. 2018 (2018) - 2017
- [j10]Laisen Nie, Dingde Jiang, Zhihan Lv:
Modeling network traffic for traffic matrix estimation and anomaly detection based on Bayesian network in cloud computing networks. Ann. des Télécommunications 72(5-6): 297-305 (2017) - [c2]Laisen Nie, Dingde Jiang, Shui Yu, Houbing Song:
Network Traffic Prediction Based on Deep Belief Network in Wireless Mesh Backbone Networks. WCNC 2017: 1-5 - 2016
- [j9]Dingde Jiang, Laisen Nie, Zhihan Lv, Houbing Song:
Spatio-Temporal Kronecker Compressive Sensing for Traffic Matrix Recovery. IEEE Access 4: 3046-3053 (2016) - [j8]Laisen Nie, Dingde Jiang, Lei Guo, Shui Yu:
Traffic matrix prediction and estimation based on deep learning in large-scale IP backbone networks. J. Netw. Comput. Appl. 76: 16-22 (2016) - [c1]Laisen Nie, Dingde Jiang, Lei Guo, Shui Yu, Houbing Song:
Traffic Matrix Prediction and Estimation Based on Deep Learning for Data Center Networks. GLOBECOM Workshops 2016: 1-6 - 2015
- [j7]Laisen Nie, Dingde Jiang, Lei Guo:
A compressive sensing-based approach to end-to-end network traffic reconstruction utilising partial measured origin-destination flows. Trans. Emerg. Telecommun. Technol. 26(8): 1108-1117 (2015) - [j6]Laisen Nie, Dingde Jiang:
A compressive sensing-based network tomography approach to estimating origin-destination flow traffic in large-scale backbone networks. Int. J. Commun. Syst. 28(5): 889-900 (2015) - [j5]Laisen Nie, Dingde Jiang, Lei Guo:
A convex optimization-based traffic matrix estimation approach in IP-over-WDM backbone networks. J. Netw. Comput. Appl. 50: 32-38 (2015) - [j4]Laisen Nie, Dingde Jiang, Lei Guo:
End-to-End Network Traffic Reconstruction Via Network Tomography Based on Compressive Sensing. J. Netw. Syst. Manag. 23(3): 709-730 (2015) - 2014
- [j3]Laisen Nie, Dingde Jiang, Lei Guo, Zhengzheng Xu:
A reconstructing approach to end-to-end network traffic based on multifractal wavelet model. Int. J. Commun. Syst. 27(12): 3565-3580 (2014) - 2013
- [j2]Laisen Nie, Dingde Jiang, Zhengzheng Xu:
A compressive sensing-based reconstruction approach to network traffic. Comput. Electr. Eng. 39(5): 1422-1432 (2013) - [j1]Laisen Nie, Dingde Jiang, Lei Guo:
A power laws-based reconstruction approach to end-to-end network traffic. J. Netw. Comput. Appl. 36(2): 898-907 (2013)
Coauthor Index
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