| 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 | 365 | 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 | 288 | 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 | 281 | 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 10 (1), 205-216, 2024 | 119 | 2024 |
| Anomal-E: A Self-Supervised Network Intrusion Detection System Based on Graph Neural Networks E Caville, WW Lo, S Layeghy, M Portmann Knowledge-Based Systems 258, 110030, 2022 | 111 | 2022 |
| 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 | 95 | 2023 |
| 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 | 86 | 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 | 73 | 2014 |
| HBFL: A Hierarchical Blockchain-based Federated Learning Framework for a Collaborative IoT Intrusion Detection M Sarhan, WW Lo, S Layeghy, M Portmann Computers and Electrical Engineering 103, 2022 | 67 | 2022 |
| Feature Analysis for Machine Learning-based IoT Intrusion Detection M Sarhan, S Layeghy, M Portmann arXiv preprint arXiv:2108.12732, 2021 | 64 | 2021 |
| 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 | 59 | 2023 |
| Inspection-L: Self-Supervised GNN Node Embeddings for Money Laundering Detection in Bitcoin WW Lo, GK Kulatilleke, M Sarhan, S Layeghy, M Portmann Applied Intelligence, 1-12, 2023 | 58* | 2023 |
| 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 | 46 | 2016 |
| FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems MP Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo, Gayan K. Kulatilleke ... Expert Systems with Applications 241 (122564), 2024 | 45 | 2024 |
| 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 | 45 | 2021 |
| 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 | 44 | 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, 2023 | 30 | 2023 |
| Explainable Cross-domain Evaluation of ML-based Network Intrusion Detection Systems S Layeghy, M Portmann Computers and Electrical Engineering 108, 108692, 2023 | 30* | 2023 |
| Experimental Evaluation of The Impact of Dos Attacks In SDN T Alharbi, S Layeghy, M Portmann 2017 27th International Telecommunication Networks and Applications …, 2017 | 30 | 2017 |
| DI-NIDS: Domain Invariant Network Intrusion Detection System S Layeghy, M Baktashmotlagh, M Portmann Knowledge-Based Systems, 110626, 2023 | 29 | 2023 |
Marius PortmannThe University of Queenslandeecs.uq.edu.au의 이메일 확인됨