| MF-Adaboost: LDoS attack detection based on multi-features and improved Adaboost D Tang, L Tang, R Dai, J Chen, X Li, JJPC Rodrigues Future Generation Computer Systems 106, 347-359, 2020 | 110 | 2020 |
| Performance and features: Mitigating the low-rate TCP-targeted DoS attack via SDN D Tang, Y Yan, S Zhang, J Chen, Z Qin IEEE Journal on Selected Areas in Communications 40 (1), 428-444, 2021 | 58 | 2021 |
| MF-CNN: a new approach for LDoS attack detection based on multi-feature fusion and CNN D Tang, L Tang, W Shi, S Zhan, Q Yang Mobile Networks and Applications 26 (4), 1705-1722, 2021 | 50 | 2021 |
| WEDMS: An advanced mean shift clustering algorithm for LDoS attacks detection D Tang, J Man, L Tang, Y Feng, Q Yang Ad Hoc Networks 102, 102145, 2020 | 34 | 2020 |
| GASF-IPP: Detection and mitigation of LDoS attack in SDN D Tang, S Wang, B Liu, W Jin, J Zhang IEEE Transactions on Services Computing 16 (5), 3373-3384, 2023 | 32 | 2023 |
| Real-time detection and mitigation of LDoS attacks in the SDN using the HGB-FP algorithm D Tang, S Zhang, Y Yan, J Chen, Z Qin IEEE Transactions on Services Computing 15 (6), 3471-3484, 2021 | 32 | 2021 |
| The detection of low-rate DoS attacks using the SADBSCAN algorithm D Tang, S Zhang, J Chen, X Wang Information Sciences 565, 229-247, 2021 | 32 | 2021 |
| Low-rate DoS attack detection based on two-step cluster analysis and UTR analysis D Tang, R Dai, L Tang, X Li Human-centric Computing and Information Sciences 10 (1), 6, 2020 | 31 | 2020 |
| Low-rate dos attack detection based on improved logistic regression Y Yan, D Tang, S Zhan, R Dai, J Chen, N Zhu 2019 IEEE 21st International Conference on High Performance Computing and …, 2019 | 28 | 2019 |
| Pca-svm-based approach of detecting low-rate dos attack D Zhang, D Tang, L Tang, R Dai, J Chen, N Zhu 2019 IEEE 21st International Conference on High Performance Computing and …, 2019 | 25 | 2019 |
| Adaptive EWMA Method based on abnormal network traffic for LDoS attacks D Tang, K Chen, XS Chen, HY Liu, X Li Mathematical Problems in Engineering 2014 (1), 496376, 2014 | 25 | 2014 |
| ADMS: An online attack detection and mitigation system for LDoS attacks via SDN D Tang, X Wang, Y Yan, D Zhang, H Zhao Computer Communications 181, 454-471, 2022 | 24 | 2022 |
| LtRFT: Mitigate the low-rate data plane DDoS attack with learning-to-rank enabled flow tables D Tang, Y Yan, C Gao, W Liang, W Jin IEEE Transactions on Information Forensics and Security 18, 3143-3157, 2023 | 23 | 2023 |
| FR-RED: Fractal residual based real-time detection of the LDoS attack D Tang, Y Feng, S Zhang, Z Qin IEEE Transactions on Reliability 70 (3), 1143-1157, 2020 | 23 | 2020 |
| AKN-FGD: adaptive kohonen network based fine-grained detection of ldos attacks D Tang, X Wang, X Li, P Vijayakumar, N Kumar IEEE Transactions on Dependable and Secure Computing 20 (1), 273-287, 2021 | 20 | 2021 |
| Low-rate dos attacks detection based on MAF-ADM S Zhan, D Tang, J Man, R Dai, X Wang Sensors 20 (1), 189, 2019 | 18 | 2019 |
| Low-rate dos attack detection based on two-step cluster analysis D Tang, R Dai, L Tang, S Zhan, J Man International Conference on Information and Communications Security, 92-104, 2018 | 17 | 2018 |
| A low-rate dos attack detection method based on hilbert spectrum and correlation X Wu, D Tang, L Tang, J Man, S Zhan, Q Liu 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced …, 2018 | 16 | 2018 |
| SFTO-Guard: Real-time detection and mitigation system for slow-rate flow table overflow attacks D Tang, D Zhang, Z Qin, Q Yang, S Xiao Journal of Network and Computer Applications 213, 103597, 2023 | 13 | 2023 |
| A new detection method for LDoS attacks based on data mining D Tang, J Chen, X Wang, S Zhang, Y Yan Future Generation Computer Systems 128, 73-87, 2022 | 13 | 2022 |
