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Journal Articles
- 2024
[j10]Mohanad Sarhan
, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann:
Feature extraction for machine learning-based intrusion detection in IoT networks. Digit. Commun. Networks 10(1): 205-216 (2024)- [j9]Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Marius Portmann:
FlowTransformer: A transformer framework for flow-based network intrusion detection systems. Expert Syst. Appl. 241: 122564 (2024) - 2023
- [j8]Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann:
Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin. Appl. Intell. 53(16): 19406-19417 (2023) - [j7]Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann:
From zero-shot machine learning to zero-day attack detection. Int. J. Inf. Sec. 22(4): 947-959 (2023) - [j6]Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann:
XG-BoT: An explainable deep graph neural network for botnet detection and forensics. Internet Things 22: 100747 (2023) - [j5]Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann:
Cyber Threat Intelligence Sharing Scheme Based on Federated Learning for Network Intrusion Detection. J. Netw. Syst. Manag. 31(1): 3 (2023) - [j4]Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Mohanad Sarhan, Raja Jurdak, Marius Portmann:
Exploring edge TPU for network intrusion detection in IoT. J. Parallel Distributed Comput. 179: 104712 (2023) - 2022
- [j3]Mohanad Sarhan, Siamak Layeghy, Marius Portmann:
Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-Based Network Intrusion Detection. Big Data Res. 30: 100359 (2022) - [j2]Mohanad Sarhan, Wai Weng Lo, Siamak Layeghy, Marius Portmann:
HBFL: A hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection. Comput. Electr. Eng. 103: 108379 (2022) - [j1]Mohanad Sarhan, Siamak Layeghy, Marius Portmann:
Towards a Standard Feature Set for Network Intrusion Detection System Datasets. Mob. Networks Appl. 27(1): 357-370 (2022)
Conference and Workshop Papers
- 2023
- [c4]Mohanad Sarhan, Gayan K. Kulatilleke, Wai Weng Lo, Siamak Layeghy, Marius Portmann:
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection. CCGridW 2023: 1-7 - 2022
- [c3]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann:
Graph Neural Network-based Android Malware Classification with Jumping Knowledge. DSC 2022: 1-9 - [c2]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann:
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT. NOMS 2022: 1-9 - 2020
- [c1]Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann:
NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems. BDTA/WiCON 2020: 117-135
Informal and Other Publications
- 2023
- [i14]Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Marius Portmann:
FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems. CoRR abs/2304.14746 (2023) - 2022
- [i13]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann:
Graph Neural Network-based Android Malware Classification with Jumping Knowledge. CoRR abs/2201.07537 (2022) - [i12]Mohanad Sarhan, Wai Weng Lo, Siamak Layeghy, Marius Portmann:
HBFL: A Hierarchical Blockchain-based Federated Learning Framework for a Collaborative IoT Intrusion Detection. CoRR abs/2204.04254 (2022) - [i11]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marius Portmann:
XG-BoT: An Explainable Deep Graph Neural Network for Botnet Detection and Forensics. CoRR abs/2207.09088 (2022) - [i10]Mohanad Sarhan, Gayan K. Kulatilleke, Wai Weng Lo, Siamak Layeghy, Marius Portmann:
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection. CoRR abs/2212.07558 (2022) - 2021
- [i9]Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann:
Towards a Standard Feature Set of NIDS Datasets. CoRR abs/2101.11315 (2021) - [i8]Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Mohanad Sarhan, Raja Jurdak, Marius Portmann:
Exploring Edge TPU for Network Intrusion Detection in IoT. CoRR abs/2103.16295 (2021) - [i7]Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann:
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System. CoRR abs/2103.16329 (2021) - [i6]Mohanad Sarhan, Siamak Layeghy, Marius Portmann:
An Explainable Machine Learning-based Network Intrusion Detection System for Enabling Generalisability in Securing IoT Networks. CoRR abs/2104.07183 (2021) - [i5]Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann:
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks. CoRR abs/2108.12722 (2021) - [i4]Mohanad Sarhan, Siamak Layeghy, Marius Portmann:
Feature Analysis for ML-based IIoT Intrusion Detection. CoRR abs/2108.12732 (2021) - [i3]Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann:
From Zero-Shot Machine Learning to Zero-Day Attack Detection. CoRR abs/2109.14868 (2021) - [i2]Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann:
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection. CoRR abs/2111.02791 (2021) - 2020
- [i1]Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann:
NetFlow Datasets for Machine Learning-based Network Intrusion Detection Systems. CoRR abs/2011.09144 (2020)
Coauthor Index
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