Time-frequency characterization of tri-axial accelerometer data for fetal movement detection. - Mohamed Salah Khlif; Boualem Boashash; Siamak Layeghy; Taoufik Ben Jabeur; Mostefa Mesbah; Christine East; Paul B. Colditz (ISSPIT, 2011)

A time frequency approach to CFAR detection. - Siamak Layeghy; Maryam Odabaee; Mohamed Salah Khlif; H. R. Amindavar (ISSPIT, 2011)

A passive DSP approach to fetal movement detection for monitoring fetal health. - Mohamed Salah Khlif; Boualem Boashash; Siamak Layeghy; Taoufik Ben Jabeur; Paul B. Colditz; Christine East (ISSPA, 2012)

EEG amplitude and correlation spatial decay analysis for neonatal head modelling. - Maryam Odabaee; Siamak Layeghy; Mostefa Mesbah; Ghasem Azemi; Boualem Boashash; Paul B. Colditz; Sampsa Vanhatalo (ISSPA, 2012)

Non-invasivemonitoring of fetal movements using time-frequency features of accelerometry. - Siamak Layeghy; Ghasem Azemi; Paul B. Colditz; Boualem Boashash (ICASSP, 2014)

Neonatal EEG at scalp is focal and implies high skull conductivity in realistic neonatal head models. - Maryam Odabaee; Anton Tokariev; Siamak Layeghy; Mostefa Mesbah; Paul B. Colditz; Ceon Ramon; Sampsa Vanhatalo (NeuroImage, 2014)

Link capacity estimation in SDN-based end-hosts. - Anees Al-Najjar; Farzaneh Pakzad; Siamak Layeghy; Marius Portmann (ICSPCS, 2016)

SCOR: Constraint Programming-based Northbound Interface for SDN. - Siamak Layeghy; Farzaneh Pakzad; Marius Portmann (ITNAC, 2016)

Evaluation of Mininet-WiFi integration via ns-3. - Farzaneh Pakzad; Siamak Layeghy; Marius Portmann (ITNAC, 2016)

Pushing SDN to the end-host, network load balancing using OpenFlow. - Anees Al-Najjar; Siamak Layeghy; Marius Portmann (PerCom Workshops, 2016)

SCOR: Software-defined Constrained Optimal Routing Platform for SDN. - Siamak Layeghy; Farzaneh Pakzad; Marius Portmann (CoRR, 2016)

Experimental evaluation of the impact of DoS attacks in SDN. - Talal Alharbi 002; Siamak Layeghy; Marius Portmann (ITNAC, 2017)

Enhancing Quality of Experience of VoIP Traffic in SDN based End-hosts. - Anees Al-Najjar; Siamak Layeghy; Marius Portmann; Jadwiga Indulska (ITNAC, 2018)

SCOR: Software-defined Constrained Optimal Routing Platform for SDN - Siamak Layeghy (2018)

NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems. - Mohanad Sarhan; Siamak Layeghy; Nour Moustafa; Marius Portmann (BDTA/WiCON, 2020)

Deep Learning-based Cattle Activity Classification Using Joint Time-frequency Data Representation. - Seyedeh Fa'ezeh Hosseini Noorbin; Siamak Layeghy; Brano Kusy; Raja Jurdak; Greg Bishop-Hurley; Marius Portmann (CoRR, 2020)

FlowGAN - Synthetic Network Flow Generation using Generative Adversarial Networks. - Liam Daly Manocchio; Siamak Layeghy; Marius Portmann (CSE, 2021)

Scaling Spectrogram Data Representation for Deep Learning on Edge TPU. - Seyedehfaezeh Hosseininoorbin; Siamak Layeghy; Brano Kusy; Raja Jurdak; Marius Portmann (PerCom Workshops, 2021)

Deep learning-based cattle behaviour classification using joint time-frequency data representation. - Seyedehfaezeh Hosseininoorbin; Siamak Layeghy; Brano Kusy; Raja Jurdak; Greg Bishop-Hurley; Paul L. Greenwood; Marius Portmann (Comput. Electron. Agric., 2021)

Automatic fetal movement recognition from multi-channel accelerometry data. - Mostefa Mesbah; Mohamed Salah Khlif; Siamak Layeghy; Christine East; Shiying Dong; Amy Brodtmann; Paul B. Colditz; Boualem Boashash (Comput. Methods Programs Biomed., 2021)

Towards a Standard Feature Set of NIDS Datasets. - Mohanad Sarhan; Siamak Layeghy; Nour Moustafa; Marius Portmann (CoRR, 2021)

E-GraphSAGE: A Graph Neural Network based Intrusion Detection System. - Wai Weng Lo; Siamak Layeghy; Mohanad Sarhan; Marcus Gallagher; Marius Portmann (CoRR, 2021)

An Explainable Machine Learning-based Network Intrusion Detection System for Enabling Generalisability in Securing IoT Networks. - Mohanad Sarhan; Siamak Layeghy; Marius Portmann (CoRR, 2021)

Benchmarking the Benchmark - Analysis of Synthetic NIDS Datasets. - Siamak Layeghy; Marcus Gallagher; Marius Portmann (CoRR, 2021)

Feature Analysis for ML-based IIoT Intrusion Detection. - Mohanad Sarhan; Siamak Layeghy; Marius Portmann (CoRR, 2021)

Exploring Deep Neural Networks on Edge TPU. - Seyedehfaezeh Hosseininoorbin; Siamak Layeghy; Brano Kusy; Raja Jurdak; Marius Portmann (CoRR, 2021)

P-SCOR: Integration of Constraint Programming Orchestration and Programmable Data Plane. - Andrea Melis 001; Siamak Layeghy; Davide Berardi; Marius Portmann; Marco Prandini; Franco Callegati (IEEE Trans. Netw. Serv. Manag., 2021)

Graph Neural Network-based Android Malware Classification with Jumping Knowledge. - Wai Weng Lo; Siamak Layeghy; Mohanad Sarhan; Marcus Gallagher; Marius Portmann (DSC, 2022)

Network Intrusion Detection System in a Light Bulb. - Liam Daly Manocchio; Siamak Layeghy; Marius Portmann (ITNAC, 2022)

E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT. - Wai Weng Lo; Siamak Layeghy; Mohanad Sarhan; Marcus Gallagher; Marius Portmann (NOMS, 2022)

Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-Based Network Intrusion Detection. - Mohanad Sarhan; Siamak Layeghy; Marius Portmann (Big Data Res., 2022)

HBFL: A hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection. - Mohanad Sarhan; Wai Weng Lo; Siamak Layeghy; Marius Portmann (Comput. Electr. Eng., 2022)

Inspection-L: Practical GNN-Based Money Laundering Detection System for Bitcoin. - Wai Weng Lo; Siamak Layeghy; Marius Portmann (CoRR, 2022)

On Generalisability of Machine Learning-based Network Intrusion Detection Systems. - Siamak Layeghy; Marius Portmann (CoRR, 2022)

XG-BoT: An Explainable Deep Graph Neural Network for Botnet Detection and Forensics. - Wai Weng Lo; Siamak Layeghy; Mohanad Sarhan; Marius Portmann (CoRR, 2022)

Anomal-E: A self-supervised network intrusion detection system based on graph neural networks. - Evan Caville; Wai Weng Lo; Siamak Layeghy; Marius Portmann (Knowl. Based Syst., 2022)

Towards a Standard Feature Set for Network Intrusion Detection System Datasets. - Mohanad Sarhan; Siamak Layeghy; Marius Portmann (Mob. Networks Appl., 2022)

DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection. - Mohanad Sarhan; Gayan K. Kulatilleke; Wai Weng Lo; Siamak Layeghy; Marius Portmann (CCGridW, 2023)

From zero-shot machine learning to zero-day attack detection. - Mohanad Sarhan; Siamak Layeghy; Marcus Gallagher; Marius Portmann (Int. J. Inf. Sec., 2023)

Cyber Threat Intelligence Sharing Scheme Based on Federated Learning for Network Intrusion Detection. - Mohanad Sarhan; Siamak Layeghy; Nour Moustafa; Marius Portmann (J. Netw. Syst. Manag., 2023)

DI-NIDS: Domain invariant network intrusion detection system. - Siamak Layeghy; Mahsa Baktashmotlagh; Marius Portmann (Knowl. Based Syst., 2023)

Explainable Cross-domain Evaluation of ML-based Network Intrusion Detection Systems. - Siamak Layeghy; Marius Portmann (Comput. Electr. Eng., 2023)

Exploring Edge TPU for deep feed-forward neural networks. - Seyedehfaezeh Hosseininoorbin; Siamak Layeghy; Brano Kusy; Raja Jurdak; Marius Portmann (Internet Things, 2023)

HARBIC: Human activity recognition using bi-stream convolutional neural network with dual joint time-frequency representation. - Seyedehfaezeh Hosseininoorbin; Siamak Layeghy; Brano Kusy; Raja Jurdak; Marius Portmann (Internet Things, 2023)

XG-BoT: An explainable deep graph neural network for botnet detection and forensics. - Wai Weng Lo; Gayan K. Kulatilleke; Mohanad Sarhan; Siamak Layeghy; Marius Portmann (Internet Things, 2023)

Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin. - Wai Weng Lo; Gayan K. Kulatilleke; Mohanad Sarhan; Siamak Layeghy; Marius Portmann (Appl. Intell., 2023)

Exploring edge TPU for network intrusion detection in IoT. - Seyedehfaezeh Hosseininoorbin; Siamak Layeghy; Mohanad Sarhan; Raja Jurdak; Marius Portmann (J. Parallel Distributed Comput., 2023)

Towards Explainable Network Intrusion Detection using Large Language Models. - Paul R. B. Houssel; Priyanka Singh; Siamak Layeghy; Marius Portmann (BDCAT, 2024)

A configurable anonymisation approach for network flow data: Balancing utility and privacy. - Liam Daly Manocchio; Siamak Layeghy; David Gwynne; Marius Portmann (Comput. Electr. Eng., 2024)

P4-NIDS: High-Performance Network Monitoring and Intrusion Detection in P4. - Yaying Chen; Siamak Layeghy; Liam Daly Manocchio; Marius Portmann (CoRR, 2024)

Feature extraction for machine learning-based intrusion detection in IoT networks. - Mohanad Sarhan; Siamak Layeghy; Nour Moustafa; Marcus Gallagher; Marius Portmann (Digit. Commun. Networks, 2024)

FlowTransformer: A transformer framework for flow-based network intrusion detection systems. - Liam Daly Manocchio; Siamak Layeghy; Wai Weng Lo; Gayan K. Kulatilleke; Mohanad Sarhan; Marius Portmann (Expert Syst. Appl., 2024)

FlowTransformer: A flexible python framework for flow-based network data analysis. - Liam Daly Manocchio; Siamak Layeghy; Marius Portmann (Softw. Impacts, 2024)

Benchmarking the benchmark - Comparing synthetic and real-world Network IDS datasets. - Siamak Layeghy; Marcus Gallagher; Marius Portmann (J. Inf. Secur. Appl., 2024)

An empirical evaluation of preprocessing methods for machine learning based network intrusion detection systems. - Liam Daly Manocchio; Siamak Layeghy; Marcus Gallagher; Marius Portmann (Eng. Appl. Artif. Intell., 2025)

EcoShower: Estimating shower duration using non-intrusive multi-modal sensor data via LSTM and Gated Transformer models. - Lukas Sablica; Bettina Grün; Siamak Layeghy; Sara Dolnicar; Marius Portmann (Expert Syst. Appl., 2025)

Leveraging LSTM and Reinforcement Learning for Adaptive Sensing in CIoT Nodes. - Sushmita Ghosh; Siamak Layeghy; Swades De; Shouri Chatterjee; Marius Portmann (IEEE Trans. Consumer Electron., 2025)

Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems. - Majed Luay; Siamak Layeghy; Seyedehfaezeh Hosseininoorbin; Mohanad Sarhan; Nour Moustafa; Marius Portmann (CoRR, 2025)

P4-Secure: In-Band DDoS Detection in Software Defined Networks. - Liam Daly Manocchio; Yaying Chen; Siamak Layeghy; David Gwynne; Marius Portmann (IEEE Trans. Netw. Serv. Manag., 2025)

eX-NIDS: A Framework for Explainable Network Intrusion Detection Leveraging Large Language Models. - Paul R. B. Houssel; Siamak Layeghy; Priyanka Singh; Marius Portmann (CoRR, 2025)