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Featured 2024 Journal Article FlowTransformer: A transformer framework for flow-based network intrusion detection systemsManocchio, Liam Daly, Layeghy, Siamak, Lo, Wai Weng, Kulatilleke, Gayan K., Sarhan, Mohanad and Portmann, Marius (2024). FlowTransformer: A transformer framework for flow-based network intrusion detection systems. Expert Systems with Applications, 241 122564, 1-15. doi: 10.1016/j.eswa.2023.122564 |
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Featured 2024 Journal Article Benchmarking the benchmark — Comparing synthetic and real-world Network IDS datasetsLayeghy, Siamak, Gallagher, Marcus and Portmann, Marius (2024). Benchmarking the benchmark — Comparing synthetic and real-world Network IDS datasets. Journal of Information Security and Applications, 80 103689, 1-18. doi: 10.1016/j.jisa.2023.103689 |
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Featured 2023 Journal Article Exploring Edge TPU for Network Intrusion Detection in IoTHosseininoorbin, Seyedehfaezeh, Layeghy, Siamak, Sarhan, Mohanad, Jurdak, Raja and Portmann, Marius (2023). Exploring Edge TPU for Network Intrusion Detection in IoT. Journal of Parallel and Distributed Computing, 179 104712, 1-11. doi: 10.1016/j.jpdc.2023.05.001 |
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Featured 2023 Journal Article Explainable cross-domain evaluation of ML-based network intrusion detection systemsLayeghy, Siamak and Portmann, Marius (2023). Explainable cross-domain evaluation of ML-based network intrusion detection systems. Computers and Electrical Engineering, 108 108692, 1-15. doi: 10.1016/j.compeleceng.2023.108692 |
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Featured 2023 Journal Article DI-NIDS: domain invariant network intrusion detection systemLayeghy, Siamak, Baktashmotlagh, Mahsa and Portmann, Marius (2023). DI-NIDS: domain invariant network intrusion detection system. Knowledge-Based Systems, 273 110626, 110626. doi: 10.1016/j.knosys.2023.110626 |
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Featured 2022 Journal Article Anomal-E: A self-supervised network intrusion detection system based on graph neural networksCaville, Evan, Lo, Wai Weng, Layeghy, Siamak and Portmann, Marius (2022). Anomal-E: A self-supervised network intrusion detection system based on graph neural networks. Knowledge-Based Systems, 258 110030, 1-11. doi: 10.1016/j.knosys.2022.110030 |
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Featured 2022 Conference Publication E-GraphSAGE: a graph neural network based intrusion detection system for IoTLo, Wai Weng, Layeghy, Siamak, Sarhan, Mohanad, Gallagher, Marcus and Portmann, Marius (2022). E-GraphSAGE: a graph neural network based intrusion detection system for IoT. NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary, 25-29 April 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/noms54207.2022.9789878 |
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Featured 2021 Conference Publication NetFlow datasets for machine learning-based network intrusion detection systemsSarhan, Mohanad, Layeghy, Siamak, Moustafa, Nour and Portmann, Marius (2021). NetFlow datasets for machine learning-based network intrusion detection systems. 10th EAI International Conference, BDTA 2020 and 13th EAI International Conference on Wireless Internet, WiCON 2020, Virtual Event, 11 December 2020. Cham, Switzerland: Springer Science and Business Media Deutschland GmbH. doi: 10.1007/978-3-030-72802-1_9 |
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2025 Journal Article EcoShower: estimating shower duration using non-intrusive multi-modal sensor data via LSTM and Gated Transformer modelsSablica, Lukas, Grün, Bettina, Layeghy, Siamak, Dolnicar, Sara and Portmann, Marius (2025). EcoShower: estimating shower duration using non-intrusive multi-modal sensor data via LSTM and Gated Transformer models. Expert Systems with Applications, 277 127202, 127202-277. doi: 10.1016/j.eswa.2025.127202 |
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2025 Journal Article P4-Secure: in-band DDoS detection in software defined networksDaly Manocchio, Liam, Chen, Yaying, Layeghy, Siamak, Gwynne, David and Portmann, Marius (2025). P4-Secure: in-band DDoS detection in software defined networks. IEEE Transactions on Network and Service Management, PP (99), 1-1. doi: 10.1109/tnsm.2025.3552844 |
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2025 Other Outputs NF-ToN-IoT-v3Luay, Majed, Layeghy, Siamak, Mohanad, Sarhan, Sayedehfaezeh, Hoseininoorbin, Moustafa, Nour and Portmann, Marius (2025). NF-ToN-IoT-v3. The University of Queensland. (Dataset) doi: 10.48610/44d7c5e |
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2025 Other Outputs NF-UNSW-NB15-v3Luay, Majed, Layeghy, Siamak, Mohanad, Sarhan, Sayedehfaezeh, Hoseininoorbin, Moustafa, Nour and Portmann, Marius (2025). NF-UNSW-NB15-v3. The University of Queensland. (Dataset) doi: 10.48610/6e0eda1 |
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2025 Other Outputs NF-CSE-CIC-IDS2018-v3Luay, Majed, Layeghy, Siamak, Mohanad, Sarhan, Sayedehfaezeh, Hoseininoorbin, Moustafa, Nour and Portmann, Marius (2025). NF-CSE-CIC-IDS2018-v3. The University of Queensland. (Dataset) doi: 10.48610/ece9b83 |
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2025 Other Outputs NF-BoT-IoT-v3Luay, Majed, Layeghy, Siamak, Mohanad, Sarhan, Sayedehfaezeh, Hoseininoorbin, Nour, Moustafa and Portmann, Marius (2025). NF-BoT-IoT-v3. The University of Queensland. (Dataset) doi: 10.48610/73c4ebc |
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2024 Journal Article Does every hotel room need a minifridge? Empirical evidence from consumer self-reports and an automatic sensor-based system measuring electricity consumption and guest useDolnicar, Sara, Greene, Danyelle, Layeghy, Siamak and Portmann, Marius (2024). Does every hotel room need a minifridge? Empirical evidence from consumer self-reports and an automatic sensor-based system measuring electricity consumption and guest use. Annals of Tourism Research Empirical Insights, 5 (2) 100134. doi: 10.1016/j.annale.2024.100134 |
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2024 Journal Article FlowTransformer: A flexible python framework for flow-based network data analysisManocchio, Liam Daly, Layeghy, Siamak and Portmann, Marius (2024). FlowTransformer: A flexible python framework for flow-based network data analysis. Software Impacts, 22 100702, 100702. doi: 10.1016/j.simpa.2024.100702 |
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2024 Journal Article A configurable anonymisation approach for network flow data: Balancing utility and privacyManocchio, Liam Daly, Layeghy, Siamak, Gwynne, David and Portmann, Marius (2024). A configurable anonymisation approach for network flow data: Balancing utility and privacy. Computers and Electrical Engineering, 118 109465, 1-16. doi: 10.1016/j.compeleceng.2024.109465 |
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2024 Journal Article Feature extraction for machine learning-based intrusion detection in IoT networksSarhan, Mohanad, Layeghy, Siamak, Moustafa, Nour, Gallagher, Marcus and Portmann, Marius (2024). Feature extraction for machine learning-based intrusion detection in IoT networks. Digital Communications and Networks, 10 (1), 205-216. doi: 10.1016/j.dcan.2022.08.012 |
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2024 Journal Article Leveraging LSTM and Reinforcement Learning for Adaptive Sensing in CIoT NodesGhosh, Sushmita, Layeghy, Siamak, De, Swades, Chatterjee, Shouri and Portmann, Marius (2024). Leveraging LSTM and Reinforcement Learning for Adaptive Sensing in CIoT Nodes. IEEE Transactions on Consumer Electronics, 1-1. doi: 10.1109/tce.2024.3516498 |
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2023 Journal Article XG-BoT: an explainable deep graph neural network for botnet detection and forensicsLo, Wai Weng, Kulatilleke, Gayan, Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). XG-BoT: an explainable deep graph neural network for botnet detection and forensics. Internet of Things, 22 100747, 100747. doi: 10.1016/j.iot.2023.100747 |
