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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, 100134. doi: 10.1016/j.annale.2024.100134 |
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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 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, 122564. doi: 10.1016/j.eswa.2023.122564 |
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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 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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2023 Journal Article Efficient block contrastive learning via parameter-free meta-node approximationKulatilleke, Gayan K., Portmann, Marius and Chandra, Shekhar S. (2023). Efficient block contrastive learning via parameter-free meta-node approximation. Neurocomputing, 561 126850. doi: 10.1016/j.neucom.2023.126850 |
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2023 Journal Article Automatically monitoring environmental performance in tourism – The example of plate waste at all-you-can-eat buffetsDolnicar, Sara, Gray, Angus, Grün, Bettina, Li, Hongwei and Portmann, Marius (2023). Automatically monitoring environmental performance in tourism – The example of plate waste at all-you-can-eat buffets. Annals of Tourism Research Empirical Insights, 4 (2) 100100, 1-3. doi: 10.1016/j.annale.2023.100100 |
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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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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 |
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2023 Journal Article HARBIC: Human activity recognition using bi-stream convolutional neural network with dual joint time-frequency representationHosseininoorbin, Seyedehfaezeh, Layeghy, Siamak, Kusy, Brano, Jurdak, Raja and Portmann, Marius (2023). HARBIC: Human activity recognition using bi-stream convolutional neural network with dual joint time-frequency representation. Internet of Things, 22 100816, 1-17. doi: 10.1016/j.iot.2023.100816 |
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2023 Journal Article Exploring Edge TPU for deep feed-forward neural networksHosseininoorbin, Seyedehfaezeh, Layeghy, Siamak, Kusy, Brano, Jurdak, Raja and Portmann, Marius (2023). Exploring Edge TPU for deep feed-forward neural networks. Internet of Things, 22 100749, 1-16. doi: 10.1016/j.iot.2023.100749 |
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2023 Journal Article Light-Weight ML Aided Autonomous IoT NetworksGhosh, Sushmita, Mandal, Akash Kumar, De, Swades, Chatterjee, Shouri and Portmann, Marius (2023). Light-Weight ML Aided Autonomous IoT Networks. IEEE Communications Magazine, 61 (6), 51-57. doi: 10.1109/mcom.001.2200539 |
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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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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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2023 Journal Article FusedAR: energy-positive human activity recognition using kinetic and solar signal fusionSandhu, Muhammad Moid, Khalifa, Sara, Geissdoerfer, Kai, Jurdak, Raja, Portmann, Marius and Kusy, Brano (2023). FusedAR: energy-positive human activity recognition using kinetic and solar signal fusion. IEEE Sensors Journal, 23 (11), 12411-12426. doi: 10.1109/jsen.2023.3268687 |
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2023 Journal Article From zero-shot machine learning to zero-day attack detectionSarhan, Mohanad, Layeghy, Siamak, Gallagher, Marcus and Portmann, Marius (2023). From zero-shot machine learning to zero-day attack detection. International Journal of Information Security, 22 (4), 947-959. doi: 10.1007/s10207-023-00676-0 |
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2023 Journal Article Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoinLo, Wai Weng, Kulatilleke, Gayan K., Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin. Applied Intelligence, 53 (16), 1-12. doi: 10.1007/s10489-023-04504-9 |
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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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2022 Journal Article Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-Based Network Intrusion DetectionSarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2022). Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-Based Network Intrusion Detection. Big Data Research, 30 100359, 1-9. doi: 10.1016/j.bdr.2022.100359 |
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2022 Journal Article Cyber threat intelligence sharing scheme based on federated learning for network intrusion detectionSarhan, Mohanad, Layeghy, Siamak, Moustafa, Nour and Portmann, Marius (2022). Cyber threat intelligence sharing scheme based on federated learning for network intrusion detection. Journal of Network and Systems Management, 31 (1) 3. doi: 10.1007/s10922-022-09691-3 |
