Siamak Layeghy

75 papers B 1C 1Misc 6Journal 55Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LLMs can pass the CCNA certification exam but do they understand networking? Comput. Networks Liam Daly Manocchio, Siamak Layeghy, Paul R. B. Houssel, Marius Portmann
2026	J	`jnl`	eX-NIDS: A framework for explainable network intrusion detection leveraging Large Language Models. Comput. Electr. Eng. Paul R. B. Houssel, Siamak Layeghy, Priyanka Singh, Marius Portmann
2025	J	`jnl`	An empirical evaluation of preprocessing methods for machine learning based network intrusion detection systems. Eng. Appl. Artif. Intell. Liam Daly Manocchio, Siamak Layeghy, Marcus Gallagher, Marius Portmann
2025	J	`jnl`	EcoShower: Estimating shower duration using non-intrusive multi-modal sensor data via LSTM and Gated Transformer models. Expert Syst. Appl. Lukas Sablica, Bettina Grün, Siamak Layeghy, Sara Dolnicar, Marius Portmann
2025	J	`jnl`	Leveraging LSTM and Reinforcement Learning for Adaptive Sensing in CIoT Nodes. IEEE Trans. Consumer Electron. Sushmita Ghosh, Siamak Layeghy, Swades De, Shouri Chatterjee, Marius Portmann
2025	J	`jnl`	P4-Secure: In-Band DDoS Detection in Software Defined Networks. IEEE Trans. Netw. Serv. Manag. Liam Daly Manocchio, Yaying Chen, Siamak Layeghy, David Gwynne, Marius Portmann
2025	J	`jnl`	Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems. CoRR Majed Luay, Siamak Layeghy, Seyedehfaezeh Hosseininoorbin, Mohanad Sarhan, Nour Moustafa, Marius Portmann
2025	J	`jnl`	eX-NIDS: A Framework for Explainable Network Intrusion Detection Leveraging Large Language Models. CoRR Paul R. B. Houssel, Siamak Layeghy, Priyanka Singh, Marius Portmann
2024	J	`jnl`	A configurable anonymisation approach for network flow data: Balancing utility and privacy. Comput. Electr. Eng. Liam Daly Manocchio, Siamak Layeghy, David Gwynne, Marius Portmann
2024	J	`jnl`	Benchmarking the benchmark - Comparing synthetic and real-world Network IDS datasets. J. Inf. Secur. Appl. Siamak Layeghy, Marcus Gallagher, Marius Portmann
2024	J	`jnl`	Feature extraction for machine learning-based intrusion detection in IoT networks. Digit. Commun. Networks Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann
2024	J	`jnl`	FlowTransformer: A flexible python framework for flow-based network data analysis. Softw. Impacts Liam Daly Manocchio, Siamak Layeghy, Marius Portmann
2024	J	`jnl`	FlowTransformer: A transformer framework for flow-based network intrusion detection systems. Expert Syst. Appl. Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Marius Portmann
2024	J	`jnl`	P4-NIDS: High-Performance Network Monitoring and Intrusion Detection in P4. CoRR Yaying Chen, Siamak Layeghy, Liam Daly Manocchio, Marius Portmann
2024	C	`conf`	Towards Explainable Network Intrusion Detection using Large Language Models. BDCAT Paul R. B. Houssel, Priyanka Singh, Siamak Layeghy, Marius Portmann
2024	J	`jnl`	Towards Explainable Network Intrusion Detection using Large Language Models. CoRR Paul R. B. Houssel, Priyanka Singh, Siamak Layeghy, Marius Portmann
2023	J	`jnl`	Cyber Threat Intelligence Sharing Scheme Based on Federated Learning for Network Intrusion Detection. J. Netw. Syst. Manag. Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann
2023	J	`jnl`	DI-NIDS: Domain invariant network intrusion detection system. Knowl. Based Syst. Siamak Layeghy, Mahsa Baktashmotlagh, Marius Portmann
2023	—	`conf`	DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection. CCGridW Mohanad Sarhan, Gayan K. Kulatilleke, Wai Weng Lo, Siamak Layeghy, Marius Portmann
2023	J	`jnl`	Explainable Cross-domain Evaluation of ML-based Network Intrusion Detection Systems. Comput. Electr. Eng. Siamak Layeghy, Marius Portmann
2023	J	`jnl`	Exploring Edge TPU for deep feed-forward neural networks. Internet Things Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Brano Kusy, Raja Jurdak, Marius Portmann
2023	J	`jnl`	Exploring edge TPU for network intrusion detection in IoT. J. Parallel Distributed Comput. Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Mohanad Sarhan, Raja Jurdak, Marius Portmann
2023	J	`jnl`	FlowTransformer: A Transformer Framework for Flow-based Network Intrusion Detection Systems. CoRR Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Marius Portmann
2023	J	`jnl`	From zero-shot machine learning to zero-day attack detection. Int. J. Inf. Sec. Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann
2023	J	`jnl`	HARBIC: Human activity recognition using bi-stream convolutional neural network with dual joint time-frequency representation. Internet Things Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Brano Kusy, Raja Jurdak, Marius Portmann
2023	J	`jnl`	Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin. Appl. Intell. Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann
2023	J	`jnl`	XG-BoT: An explainable deep graph neural network for botnet detection and forensics. Internet Things Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann
2022	J	`jnl`	Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural Networks. CoRR Evan Caville, Wai Weng Lo, Siamak Layeghy, Marius Portmann
2022	J	`jnl`	Anomal-E: A self-supervised network intrusion detection system based on graph neural networks. Knowl. Based Syst. Evan Caville, Wai Weng Lo, Siamak Layeghy, Marius Portmann
2022	J	`jnl`	DI-NIDS: Domain Invariant Network Intrusion Detection System. CoRR Siamak Layeghy, Mahsa Baktashmotlagh, Marius Portmann
2022	J	`jnl`	DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection. CoRR Mohanad Sarhan, Gayan K. Kulatilleke, Wai Weng Lo, Siamak Layeghy, Marius Portmann
2022	B	`conf`	E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT. NOMS Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
2022	J	`jnl`	Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-Based Network Intrusion Detection. Big Data Res. Mohanad Sarhan, Siamak Layeghy, Marius Portmann
2022	—	`conf`	Graph Neural Network-based Android Malware Classification with Jumping Knowledge. DSC Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
2022	J	`jnl`	Graph Neural Network-based Android Malware Classification with Jumping Knowledge. CoRR Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
2022	J	`jnl`	HBFL: A Hierarchical Blockchain-based Federated Learning Framework for a Collaborative IoT Intrusion Detection. CoRR Mohanad Sarhan, Wai Weng Lo, Siamak Layeghy, Marius Portmann
2022	J	`jnl`	HBFL: A hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection. Comput. Electr. Eng. Mohanad Sarhan, Wai Weng Lo, Siamak Layeghy, Marius Portmann
2022	J	`jnl`	Inspection-L: Practical GNN-Based Money Laundering Detection System for Bitcoin. CoRR Wai Weng Lo, Siamak Layeghy, Marius Portmann
2022	Misc	`conf`	Network Intrusion Detection System in a Light Bulb. ITNAC Liam Daly Manocchio, Siamak Layeghy, Marius Portmann
2022	J	`jnl`	Network Intrusion Detection System in a Light Bulb. CoRR Liam Daly Manocchio, Siamak Layeghy, Marius Portmann
2022	J	`jnl`	On Generalisability of Machine Learning-based Network Intrusion Detection Systems. CoRR Siamak Layeghy, Marius Portmann
2022	J	`jnl`	Towards a Standard Feature Set for Network Intrusion Detection System Datasets. Mob. Networks Appl. Mohanad Sarhan, Siamak Layeghy, Marius Portmann
2022	J	`jnl`	XG-BoT: An Explainable Deep Graph Neural Network for Botnet Detection and Forensics. CoRR Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marius Portmann
2021	J	`jnl`	A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection. CoRR Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann
2021	J	`jnl`	An Explainable Machine Learning-based Network Intrusion Detection System for Enabling Generalisability in Securing IoT Networks. CoRR Mohanad Sarhan, Siamak Layeghy, Marius Portmann
2021	J	`jnl`	Automatic fetal movement recognition from multi-channel accelerometry data. Comput. Methods Programs Biomed. Mostefa Mesbah, Mohamed Salah Khlif, Siamak Layeghy, Christine East, Shiying Dong, Amy Brodtmann, Paul B. Colditz, Boualem Boashash
2021	J	`jnl`	Benchmarking the Benchmark - Analysis of Synthetic NIDS Datasets. CoRR Siamak Layeghy, Marcus Gallagher, Marius Portmann
2021	J	`jnl`	Deep learning-based cattle behaviour classification using joint time-frequency data representation. Comput. Electron. Agric. Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Brano Kusy, Raja Jurdak, Greg Bishop-Hurley, Paul L. Greenwood, Marius Portmann
2021	J	`jnl`	E-GraphSAGE: A Graph Neural Network based Intrusion Detection System. CoRR Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
2021	J	`jnl`	Exploring Deep Neural Networks on Edge TPU. CoRR Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Brano Kusy, Raja Jurdak, Marius Portmann
2021	J	`jnl`	Exploring Edge TPU for Network Intrusion Detection in IoT. CoRR Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Mohanad Sarhan, Raja Jurdak, Marius Portmann
2021	J	`jnl`	Feature Analysis for ML-based IIoT Intrusion Detection. CoRR Mohanad Sarhan, Siamak Layeghy, Marius Portmann
2021	J	`jnl`	Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks. CoRR Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marcus Gallagher, Marius Portmann
2021	—	`conf`	FlowGAN - Synthetic Network Flow Generation using Generative Adversarial Networks. CSE Liam Daly Manocchio, Siamak Layeghy, Marius Portmann
2021	J	`jnl`	From Zero-Shot Machine Learning to Zero-Day Attack Detection. CoRR Mohanad Sarhan, Siamak Layeghy, Marcus Gallagher, Marius Portmann
2021	J	`jnl`	P-SCOR: Integration of Constraint Programming Orchestration and Programmable Data Plane. IEEE Trans. Netw. Serv. Manag. Andrea Melis, Siamak Layeghy, Davide Berardi, Marius Portmann, Marco Prandini, Franco Callegati
2021	—	`conf`	Scaling Spectrogram Data Representation for Deep Learning on Edge TPU. PerCom Workshops Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Brano Kusy, Raja Jurdak, Marius Portmann
2021	J	`jnl`	Towards a Standard Feature Set of NIDS Datasets. CoRR Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann
2020	J	`jnl`	Deep Learning-based Cattle Activity Classification Using Joint Time-frequency Data Representation. CoRR Seyedeh Fa'ezeh Hosseini Noorbin, Siamak Layeghy, Brano Kusy, Raja Jurdak, Greg Bishop-Hurley, Marius Portmann
2020	—	`conf`	NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems. BDTA/WiCON Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann
2020	J	`jnl`	NetFlow Datasets for Machine Learning-based Network Intrusion Detection Systems. CoRR Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann
2018	Misc	`conf`	Enhancing Quality of Experience of VoIP Traffic in SDN based End-hosts. ITNAC Anees Al-Najjar, Siamak Layeghy, Marius Portmann, Jadwiga Indulska
2018	—	`—`	SCOR: Software-defined Constrained Optimal Routing Platform for SDN Siamak Layeghy
2017	Misc	`conf`	Experimental evaluation of the impact of DoS attacks in SDN. ITNAC Talal Alharbi, Siamak Layeghy, Marius Portmann
2016	Misc	`conf`	Evaluation of Mininet-WiFi integration via ns-3. ITNAC Farzaneh Pakzad, Siamak Layeghy, Marius Portmann
2016	—	`conf`	Link capacity estimation in SDN-based end-hosts. ICSPCS Anees Al-Najjar, Farzaneh Pakzad, Siamak Layeghy, Marius Portmann
2016	—	`conf`	Pushing SDN to the end-host, network load balancing using OpenFlow. PerCom Workshops Anees Al-Najjar, Siamak Layeghy, Marius Portmann
2016	Misc	`conf`	SCOR: Constraint Programming-based Northbound Interface for SDN. ITNAC Siamak Layeghy, Farzaneh Pakzad, Marius Portmann
2016	J	`jnl`	SCOR: Software-defined Constrained Optimal Routing Platform for SDN. CoRR Siamak Layeghy, Farzaneh Pakzad, Marius Portmann
2014	J	`jnl`	Neonatal EEG at scalp is focal and implies high skull conductivity in realistic neonatal head models. NeuroImage Maryam Odabaee, Anton Tokariev, Siamak Layeghy, Mostefa Mesbah, Paul B. Colditz, Ceon Ramon, Sampsa Vanhatalo
2014	Misc	`conf`	Non-invasivemonitoring of fetal movements using time-frequency features of accelerometry. ICASSP Siamak Layeghy, Ghasem Azemi, Paul B. Colditz, Boualem Boashash
2012	—	`conf`	A passive DSP approach to fetal movement detection for monitoring fetal health. ISSPA Mohamed Salah Khlif, Boualem Boashash, Siamak Layeghy, Taoufik Ben Jabeur, Paul B. Colditz, Christine East
2012	—	`conf`	EEG amplitude and correlation spatial decay analysis for neonatal head modelling. ISSPA Maryam Odabaee, Siamak Layeghy, Mostefa Mesbah, Ghasem Azemi, Boualem Boashash, Paul B. Colditz, Sampsa Vanhatalo
2011	—	`conf`	A time frequency approach to CFAR detection. ISSPIT Siamak Layeghy, Maryam Odabaee, Mohamed Salah Khlif, H. R. Amindavar
2011	—	`conf`	Time-frequency characterization of tri-axial accelerometer data for fetal movement detection. ISSPIT Mohamed Salah Khlif, Boualem Boashash, Siamak Layeghy, Taoufik Ben Jabeur, Mostefa Mesbah, Christine East, Paul B. Colditz