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 | 239 | 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 | 167 | 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 | 165 | 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 | 69 | 2014 |
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 | 66 | 2022 |
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 | 58 | 2022 |
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 | 56 | 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 | 52 | 2023 |
Feature Analysis for Machine Learning-based IoT Intrusion Detection M Sarhan, S Layeghy, M Portmann arXiv preprint arXiv:2108.12732, 2021 | 51 | 2021 |
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 | 44 | 2022 |
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 | 44 | 2016 |
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 | 36 | 2021 |
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 | 32* | 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 | 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 | 27 | 2017 |
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 | 26 | 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 | 26 | 2023 |
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 | 25 | 2011 |
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 | 23 | 2014 |
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 | 23 | 2012 |