Traffic engineering in SDN/OSPF hybrid network Y Guo, Z Wang, X Yin, X Shi, J Wu 2014 IEEE 22nd international conference on network protocols, 563-568, 2014 | 179 | 2014 |
Detecting prefix hijackings in the internet with argus X Shi, Y Xiang, Z Wang, X Yin, J Wu Proceedings of the 2012 Internet Measurement Conference, 15-28, 2012 | 163 | 2012 |
HELAD: A novel network anomaly detection model based on heterogeneous ensemble learning Y Zhong, W Chen, Z Wang, Y Chen, K Wang, Y Li, X Yin, X Shi, J Yang, ... Computer Networks 169, 107049, 2020 | 141 | 2020 |
Evaluating and improving adversarial robustness of machine learning-based network intrusion detectors D Han, Z Wang, Y Zhong, W Chen, J Yang, S Lu, X Shi, X Yin IEEE Journal on Selected Areas in Communications 39 (8), 2632-2647, 2021 | 92 | 2021 |
Deepaid: Interpreting and improving deep learning-based anomaly detection in security applications D Han, Z Wang, W Chen, Y Zhong, S Wang, H Zhang, J Yang, X Shi, ... Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 61 | 2021 |
A survey on network verification and testing with formal methods: Approaches and challenges Y Li, X Yin, Z Wang, J Yao, X Shi, J Wu, H Zhang, Q Wang IEEE Communications Surveys & Tutorials 21 (1), 940-969, 2018 | 53 | 2018 |
Incremental deployment for traffic engineering in hybrid SDN network Y Guo, Z Wang, X Yin, X Shi, J Wu, H Zhang 2015 IEEE 34th international performance computing and communications …, 2015 | 53 | 2015 |
Log-based anomaly detection with robust feature extraction and online learning S Han, Q Wu, H Zhang, B Qin, J Hu, X Shi, L Liu, X Yin IEEE Transactions on Information Forensics and Security 16, 2300-2311, 2021 | 51 | 2021 |
Threatrace: Detecting and tracing host-based threats in node level through provenance graph learning S Wang, Z Wang, T Zhou, H Sun, X Yin, D Han, H Zhang, X Shi, J Yang IEEE Transactions on Information Forensics and Security 17, 3972-3987, 2022 | 47 | 2022 |
Traffic engineering in hybrid SDN networks with multiple traffic matrices Y Guo, Z Wang, X Yin, X Shi, J Wu Computer Networks 126, 187-199, 2017 | 42 | 2017 |
Traffic engineering in partially deployed segment routing over IPv6 network with deep reinforcement learning Y Tian, Z Wang, X Yin, X Shi, Y Guo, H Geng, J Yang IEEE/ACM Transactions on Networking 28 (4), 1573-1586, 2020 | 37 | 2020 |
Toposcope: Recover as relationships from fragmentary observations Z Jin, X Shi, Y Yang, X Yin, Z Wang, J Wu Proceedings of the ACM Internet Measurement Conference, 266-280, 2020 | 33 | 2020 |
Efficient scheduling of weighted coflows in data centers Z Wang, H Zhang, X Shi, X Yin, Y Li, H Geng, Q Wu, J Liu IEEE Transactions on Parallel and Distributed Systems 30 (9), 2003-2017, 2019 | 33 | 2019 |
Traffic matrix prediction based on deep learning for dynamic traffic engineering Z Liu, Z Wang, X Yin, X Shi, Y Guo, Y Tian 2019 IEEE Symposium on Computers and Communications (ISCC), 1-7, 2019 | 32 | 2019 |
Mutation testing of protocol messages based on extended TTCN-3 C Jing, Z Wang, X Shi, X Yin, J Wu 22nd International Conference on Advanced Information Networking and …, 2008 | 28 | 2008 |
More load, more differentiation—A design principle for deadline-aware congestion control H Zhang, X Shi, X Yin, F Ren, Z Wang 2015 IEEE Conference on Computer Communications (INFOCOM), 127-135, 2015 | 26 | 2015 |
Performance evaluation of software-defined networking with real-life isp traffic X Kong, Z Wang, X Shi, X Yin, D Li 2013 IEEE Symposium on Computers and Communications (ISCC), 000541-000547, 2013 | 26 | 2013 |
Practical traffic-space adversarial attacks on learning-based nidss D Han, Z Wang, Y Zhong, W Chen, J Yang, S Lu, X Shi, X Yin arXiv preprint arXiv:2005.07519, 2020 | 25 | 2020 |
Analysis of comparisons between OpenFlow and ForCES Z Wang, T Tsou, J Huang, X Shi, X Yin ForCES, IETF, 2012 | 25 | 2012 |
Conversational model based VoIP traffic generation L Ji, X Yin, X Shi, Z Wang International Conference on Networking and Services (ICNS'07), 14-14, 2007 | 25 | 2007 |