| NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems M Sarhan, S Layeghy, N Moustafa, M Portmann Big Data Technologies and Applications: 10th EAI International Conference …, 2021 | 137 | 2021 |
| Towards a standard feature set for network intrusion detection system datasets M Sarhan, S Layeghy, M Portmann Mobile Networks and Applications 27 (1), 357-370, 2022 | 102 | 2022 |
| E-graphsage: A graph neural network based intrusion detection system for iot WW Lo, S Layeghy, M Sarhan, M Gallagher, M Portmann NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium, 1-9, 2022 | 84 | 2022 |
| Feature Analysis for Machine Learning-based IoT Intrusion Detection M Sarhan, S Layeghy, M Portmann arXiv preprint arXiv:2108.12732, 2021 | 28 | 2021 |
| Feature extraction for machine learning-based intrusion detection in IoT networks M Sarhan, S Layeghy, N Moustafa, M Gallagher, M Portmann Digital Communications and Networks, 2022 | 24 | 2022 |
| Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection M Sarhan, S Layeghy, M Portmann arXiv preprint arXiv:2104.07183, 2021 | 22 | 2021 |
| Cyber threat intelligence sharing scheme based on federated learning for network intrusion detection M Sarhan, S Layeghy, N Moustafa, M Portmann Journal of Network and Systems Management 31 (1), 3, 2023 | 16 | 2023 |
| From zero-shot machine learning to zero-day attack detection M Sarhan, S Layeghy, M Gallagher, M Portmann International Journal of Information Security, 1-13, 2023 | 14 | 2023 |
| Exploring edge TPU for network intrusion detection in IoT S Hosseininoorbin, S Layeghy, M Sarhan, R Jurdak, M Portmann Journal of Parallel and Distributed Computing 179, 104712, 2023 | 13 | 2023 |
| HBFL: A hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection M Sarhan, WW Lo, S Layeghy, M Portmann Computers and Electrical Engineering 103, 108379, 2022 | 12 | 2022 |
| Feature analysis for ML-based IIoT intrusion detection M Sarhan, S Layeghy, M Portmann arXiv e-prints, arXiv: 2108.12732, 2021 | 11 | 2021 |
| Graph neural network-based android malware classification with jumping knowledge WW Lo, S Layeghy, M Sarhan, M Gallagher, M Portmann 2022 IEEE Conference on Dependable and Secure Computing (DSC), 1-9, 2022 | 9 | 2022 |
| XG-BoT: An explainable deep graph neural network for botnet detection and forensics WW Lo, G Kulatilleke, M Sarhan, S Layeghy, M Portmann Internet of Things 22, 100747, 2023 | 6 | 2023 |
| Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection. arXiv 2021 M Sarhan, S Layeghy, M Portmann arXiv preprint arXiv:2104.07183, 2022 | 5 | 2022 |
| Inspection-L: A Self-Supervised GNN-Based Money Laundering Detection System for Bitcoin WW Lo, M Sarhan, S Layeghy, M Portmann | 3* | |
| Towards a standard feature set of NIDS datasets. CoRR, abs/2101.11315 M Sarhan, S Layeghy, N Moustafa, M Portmann arXiv preprint arXiv:2101.11315, 2021 | 2 | 2021 |
| CIC-BoT-IoT M Sarhan, S Layeghy, M Portmann The University of Queensland, 2023 | | 2023 |
| NF-ToN-IoT-v2 M Sarhan, S Layeghy, M Portmann The University of Queensland, 2023 | | 2023 |
| NF-UQ-NIDS-v2 M Sarhan, S Layeghy The University of Queensland, 2023 | | 2023 |
| NF-UNSW-NB15-v2 M Sarhan, S Layeghy, M Portmann The University of Queensland, 2023 | | 2023 |
Siamak LayeghyUniversity of Queensland在 uq.net.au 的电子邮件经过验证
