| Malware identification using visualization images and deep learning S Ni, Q Qian, R Zhang Computers & Security 77, 871-885, 2018 | 290 | 2018 |
| Privacy preserving machine learning with homomorphic encryption and federated learning H Fang, Q Qian Future Internet 13 (4), 94, 2021 | 250 | 2021 |
| Materials informatics S Ramakrishna, TY Zhang, WC Lu, Q Qian, JSC Low, JHR Yune, DZL Tan, ... Journal of Intelligent Manufacturing 30, 2307-2326, 2019 | 139 | 2019 |
| Deep learning and visualization for identifying malware families G Sun, Q Qian IEEE Transactions on Dependable and Secure Computing 18 (1), 283-295, 2018 | 132 | 2018 |
| Different implementations of AES cryptographic algorithm G Guo, Q Qian, R Zhang 2015 IEEE 17th International Conference on High Performance Computing and …, 2015 | 51 | 2015 |
| Dynamic API call sequence visualisation for malware classification M Tang, Q Qian IET Information Security 13 (4), 367-377, 2019 | 49 | 2019 |
| A Lightweight RFID Security Protocol Based on Elliptic Curve Crytography. Q Qian, YL Jia, R Zhang Int. J. Netw. Secur. 18 (2), 354-361, 2016 | 46 | 2016 |
| Clustering Based K-anonymity Algorithm for Privacy Preservation. S Ni, M Xie, Q Qian Int. J. Netw. Secur. 19 (6), 1062-1071, 2017 | 45 | 2017 |
| Multi-objective optimization for materials design with improved NSGA-II P Zhang, Y Qian, Q Qian Materials Today Communications 28, 102709, 2021 | 42 | 2021 |
| Ontology based heterogeneous materials database integration and semantic query S Zhao, Q Qian AIP Advances 7 (10), 2017 | 38 | 2017 |
| A virtual sample generation algorithm supporting machine learning with a small-sample dataset: A case study for rubber materials L Shen, Q Qian Computational Materials Science 211, 111475, 2022 | 31 | 2022 |
| Android malware identification through visual exploration of disassembly files Y Zhao, Q Qian International Journal of Network Security 20 (6), 1061-1073, 2018 | 26 | 2018 |
| Grid-based Data Stream Clustering for Intrusion Detection. Q Qian, CJ Xiao, R Zhang Int. J. Netw. Secur. 15 (1), 1-8, 2013 | 26 | 2013 |
| Research on hidden markov model for system call anomaly detection Q Qian, M Xin Intelligence and Security Informatics: Pacific Asia Workshop, PAISI 2007 …, 2007 | 26 | 2007 |
| Malicious behavior analysis for android applications Q Qian, J Cai, M Xie, R Zhang International Journal of Network Security 18 (1), 182-192, 2016 | 24 | 2016 |
| Entropy based method for network anomaly detection Q Quan, C Hong-Yi, Z Rui 2009 15th IEEE Pacific Rim International Symposium on Dependable Computing …, 2009 | 23 | 2009 |
| Malicious code classification based on opcode sequences and textCNN network Q Wang, Q Qian Journal of Information Security and Applications 67, 103151, 2022 | 21 | 2022 |
| Intrusion detection based on neural networks and artificial bee colony algorithm Q Qian, J Cai, R Zhang 2014 IEEE/ACIS 13th International Conference on Computer and Information …, 2014 | 20 | 2014 |
| A density-based random forest for imbalanced data classification J Dong, Q Qian Future Internet 14 (3), 90, 2022 | 18 | 2022 |
| Federated Active Learning for Multicenter Collaborative Disease Diagnosis X Wu, J Pei, C Chen, Y Zhu, J Wang, Q Qian, J Zhang, Q Sun, Y Guo IEEE Transactions on Medical Imaging 42 (7), 2068-2080, 2022 | 17 | 2022 |
Xing WuShanghai University在 shu.edu.cn 的电子邮件经过验证
