Seuraa
Siamak Layeghy
Siamak Layeghy
University of Queensland
Vahvistettu sähköpostiosoite verkkotunnuksessa uq.edu.au - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
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
3702021
Towards a Standard Feature Set for Network Intrusion Detection System Datasets
M Sarhan, S Layeghy, M Portmann
Mobile networks and applications, 1-14, 2022
2922022
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
2912022
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
1282024
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
1132022
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
942023
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
892022
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
722014
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
672022
Feature Analysis for Machine Learning-based IoT Intrusion Detection
M Sarhan, S Layeghy, M Portmann
arXiv preprint arXiv:2108.12732, 2021
642021
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
582023
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
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
472023
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
462024
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
462016
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
452021
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
312023
Explainable Cross-domain Evaluation of ML-based Network Intrusion Detection Systems
S Layeghy, M Portmann
Computers and Electrical Engineering 108, 108692, 2023
30*2023
DI-NIDS: Domain Invariant Network Intrusion Detection System
S Layeghy, M Baktashmotlagh, M Portmann
Knowledge-Based Systems, 110626, 2023
292023
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
292022
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Artikkelit 1–20