A Novel Method of Filtering Internet Background Radiation Traffic. - Ruoyu Wang 002; Ling Zhang; Zhen Liu 017 (EIDWT, 2013)

Classifying imbalanced Internet traffic based PCDD: a per concept drift detection method. - Ruoyu Wang 002; Ling Zhang; Zhen Liu 017 (Smart Comput. Rev., 2013)

Large traffic flows classification method. - Qiong Liu; Zhen Liu 017; Ruoyu Wang 002; Changqiao Xu (ICC Workshops, 2014)

A class-oriented feature selection approach for multi-class imbalanced network traffic datasets based on local and global metrics fusion. - Zhen Liu 017; Ruoyu Wang 002; Ming Tao; Xianfa Cai (Neurocomputing, 2015)

Identifying Internet background radiation traffic based on traffic source distribution. - Ruoyu Wang 002; Zhen Liu 017; Ming Tao; Ling Zhang (J. High Speed Networks, 2015)

Research on mobile network traffic taxonomy. - Zhen Liu 017; Ruoyu Wang 002; Deyu Tang (CITS, 2016)

Mobilegt: A system to collect mobile traffic trace and build the ground truth. - Zhen Liu 017; Ruoyu Wang 002 (ITNAC, 2016)

A System for Linking Ground Truth to Mobile Network Traffic. - Zhen Liu 017; Ruoyu Wang 002; Deyu Tang; Peng Yang (MobiQuitous, 2016)

Corrigendum to "A class-oriented feature selection approach for multi-class imbalanced network traffic datasets based on local and global metrics fusion" [Neurocomputing 168 (2015) 365-381]. - Zhen Liu 017; Ruoyu Wang 002; Ming Tao; Xianfa Cai (Neurocomputing, 2016)

SmoteAdaNL: a learning method for network traffic classification. - Zhen Liu 017; Ruoyu Wang 002; Ming Tao (J. Ambient Intell. Humaniz. Comput., 2016)

Objective cost-sensitive-boosting-WELM for handling multi class imbalance problem. - Zhen Liu 017; Deyu Tang; Jincheng Li; Ruoyu Wang 002 (IJCNN, 2017)

A hybrid method based on ensemble WELM for handling multi class imbalance in cancer microarray data. - Zhen Liu 017; Deyu Tang; Yongming Cai; Ruoyu Wang 002; Fuhua Chen (Neurocomputing, 2017)

Benchmark Data for Mobile App Traffic Research. - Ruoyu Wang 002; Zhen Liu 017; Yongming Cai; Deyu Tang; Jin Yang 004; Zhao Yang (MobiQuitous, 2018)

Extending labeled mobile network traffic data by three levels traffic identification fusion. - Zhen Liu 017; Ruoyu Wang 002; Deyu Tang (Future Gener. Comput. Syst., 2018)

Adaptive learning on mobile network traffic data. - Zhen Liu 017; Nathalie Japkowicz; Ruoyu Wang 002; Deyu Tang (Connect. Sci., 2019)

Mobile app traffic flow feature extraction and selection for improving classification robustness. - Zhen Liu 017; Ruoyu Wang 002; Nathalie Japkowicz; Yongming Cai; Deyu Tang; Xianfa Cai (J. Netw. Comput. Appl., 2019)

Subconcept Based One Class Classification Method with Cluster Updating. - Zhen Liu 017; Nathalie Japkowicz; Ruoyu Wang 002 (ICMLC, 2020)

A statistical pattern based feature extraction method on system call traces for anomaly detection. - Zhen Liu 017; Nathalie Japkowicz; Ruoyu Wang 002; Yongming Cai; Deyu Tang; Xianfa Cai (Inf. Softw. Technol., 2020)

A sub-concept-based feature selection method for one-class classification. - Zhen Liu 017; Nathalie Japkowicz; Ruoyu Wang 002; Li Liu (Soft Comput., 2020)

An Unsupervised Feature Learning Method for Enhancing the Generalization of Cancer Diagnosis. - Zhen Liu 017; Ruoyu Wang 002; Wenbin Zhang 002; Deyu Tang (ICMLC, 2021)

Active Learning-Based Optimization of Scientific Experimental Design. - Ruoyu Wang 002 (CoRR, 2021)

Research on unsupervised feature learning for Android malware detection based on Restricted Boltzmann Machines. - Zhen Liu 017; Ruoyu Wang 002; Nathalie Japkowicz; Deyu Tang; Wenbin Zhang 002; Jie Zhao 011 (Future Gener. Comput. Syst., 2021)

Research on fine-tuning CNN for cancer diagnosis with gene expression data. - Zhen Liu 017; Ruoyu Wang 002; Jin Yang 004; Wenbin Zhang 002 (ICMLC, 2022)

A convolutional neural network based Android malware detection method with dynamic fine-tuning. - Zhen Liu 017; Ruoyu Wang 002; Bitao Peng; Qingqing Gan (ITNAC, 2022)

Improving the generalization of unsupervised feature learning by using data from different sources on gene expression data for cancer diagnosis. - Zhen Liu 017; Ruoyu Wang 002; Wenbin Zhang 002 (Medical Biol. Eng. Comput., 2022)

Research on Data Drift and Class Imbalance in Android Malware Detection. - Zhen Liu 017; Ruoyu Wang 002; Bitao Peng; Changji Wang; Qingqing Gan (MobiQuitous (1), 2023)

SeGDroid: An Android malware detection method based on sensitive function call graph learning. - Zhen Liu 017; Ruoyu Wang 002; Nathalie Japkowicz; Heitor Murilo Gomes; Bitao Peng; Wenbin Zhang 002 (Expert Syst. Appl., 2024)

LDCDroid: Learning data drift characteristics for handling the model aging problem in Android malware detection. - Zhen Liu 017; Ruoyu Wang 002; Bitao Peng; Lingyu Qiu; Qingqing Gan; Changji Wang; Wenbin Zhang 002 (Comput. Secur., 2025)