| 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 | 123 | 2021 |
| Towards a Standard Feature Set for Network Intrusion Detection System Datasets M Sarhan, S Layeghy, M Portmann Mobile networks and applications, 1-14, 2022 | 96 | 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 | 74 | 2022 |
| Neonatal EEG At Scalp Is Focal and Implies High Skull Conductivity in Realistic Neonatal Head Models SV Maryam Odabaee, Anton Tokariev, Siamak Layeghy NeuroImage, 2014 | 62 | 2014 |
| Pushing SDN To the End-Host, Network Load Balancing Using Openflow A Al-Najjar, S Layeghy, M Portmann 2016 IEEE international conference on pervasive computing and communication …, 2016 | 39 | 2016 |
| Experimental Evaluation of The Impact of Dos Attacks In SDN T Alharbi, S Layeghy, M Portmann 2017 27th International Telecommunication Networks and Applications …, 2017 | 27 | 2017 |
| Feature Analysis for Machine Learning-based IoT Intrusion Detection M Sarhan, S Layeghy, M Portmann arXiv preprint arXiv:2108.12732, 2021 | 25 | 2021 |
| Deep Learning-Based Cattle Behaviour Classification Using Joint Time-Frequency Data Representation S Hosseininoorbin, S Layeghy, B Kusy, R Jurdak, GJ Bishop-Hurley, ... Computers and Electronics in Agriculture 187, 106241, 2021 | 24 | 2021 |
| Time-Frequency Characterization of Tri-Axial Accelerometer Data for Fetal Movement Detection MS Khlif, B Boashash, S Layeghy, T Ben-Jabeur, M Mesbah, C East, ... 2011 IEEE International Symposium on Signal Processing and Information …, 2011 | 23 | 2011 |
| Evaluating standard feature sets towards increased generalisability and explainability of ML-based network intrusion detection M Sarhan, S Layeghy, M Portmann Big Data Research 30, 100359, 2022 | 22* | 2022 |
| 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 | 22 | 2022 |
| A Passive DSP Approach to Fetal Movement Detection for Monitoring Fetal Health MSH Khlif, B Boashash, S Layeghy, T Ben-Jabeur, PB Colditz, C East 2012 11th International Conference on Information Science, Signal Processing …, 2012 | 22 | 2012 |
| Non-invasive Monitoring of Fetal Movements Using Time-Frequency Features of Accelerometry S Layeghy, G Azemi, P Colditz, B Boashash 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 20 | 2014 |
| 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 | 15* | 2023 |
| SCOR: Software-Defined Constrained Optimal Routing Platform For SDN S Layeghy, F Pakzad, M Portmann arXiv preprint arXiv:1607.03243, 2016 | 15 | 2016 |
| Link Capacity Estimation in SDN-based End-hosts A Al-Najjar, F Pakzad, S Layeghy, M Portmann 2016 10th International Conference on Signal Processing and Communication …, 2016 | 13 | 2016 |
| SCOR: Constraint Programming-based Northbound Interface for SDN S Layeghy, F Pakzad, M Portmann 2016 26th International Telecommunication Networks and Applications …, 2016 | 13* | 2016 |
| 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, 2023 | 12 | 2023 |
| 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 | 12 | 2023 |
| Classification of Fetal Movement Accelerometry Through Time-Frequency Features S Layeghy, G Azemi, P Colditz, B Boashash 2014 8th International Conference on Signal Processing and Communication …, 2014 | 12 | 2014 |
Marius PortmannThe University of Queensland在 itee.uq.edu.au 的电子邮件经过验证
