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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 Other Outputs NF-ToN-IoT-v2Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-ToN-IoT-v2. The University of Queensland. (Dataset) doi: 10.48610/38a2d07 |
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2023 Other Outputs NF-UNSW-NB15Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-UNSW-NB15. The University of Queensland. (Dataset) doi: 10.48610/5d0832d |
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2023 Other Outputs CIC-ToN-IoTSarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). CIC-ToN-IoT. The University of Queensland. (Dataset) doi: 10.48610/f6884ce |
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2023 Other Outputs NF-UQ-NIDSSarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-UQ-NIDS. The University of Queensland. (Dataset) doi: 10.48610/69b5a53 |
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2023 Other Outputs NF-BoT-IoT-v2Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-BoT-IoT-v2. The University of Queensland. (Dataset) doi: 10.48610/ec73920 |
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2023 Other Outputs CIC-BoT-IoTSarhan, Mohanad, Layeghy, Siamak and Portmann, Marus (2023). CIC-BoT-IoT. The University of Queensland. (Dataset) doi: 10.48610/c80fccd |
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2023 Other Outputs NF-BoT-IoTSarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-BoT-IoT. The University of Queensland. (Dataset) doi: 10.48610/62e6d80 |
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2023 Other Outputs NF-UNSW-NB15-v2Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-UNSW-NB15-v2. The University of Queensland. (Dataset) doi: 10.48610/ffbb0c1 |
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2023 Other Outputs NF-ToN-IoTSarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-ToN-IoT. The University of Queensland. (Dataset) doi: 10.48610/2fa2ed6 |
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2023 Other Outputs NF-UQ-NIDS-v2Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-UQ-NIDS-v2. The University of Queensland. (Dataset) doi: 10.48610/631a24a |
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2023 Conference Publication DOC-NAD: A hybrid deep one-class classifier for network anomaly detectionSarhan, Mohanad, Kulatilleke, Gayan, Lo, Wai Weng, Layeghy, Siamak and Portmann, Marius (2023). DOC-NAD: A hybrid deep one-class classifier for network anomaly detection. 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW), Bangalore, India, 1 - 4 May 2023. Piscataway, NJ, United States: IEEE. doi: 10.1109/ccgridw59191.2023.00016 |
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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 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 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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2023 Other Outputs NF-CSE-CIC-IDS2018Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-CSE-CIC-IDS2018. The University of Queensland. (Dataset) doi: 10.48610/b9ed88b |
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2023 Other Outputs NF-CSE-CIC-IDS2018-v2Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-CSE-CIC-IDS2018-v2. The University of Queensland. (Dataset) doi: 10.48610/e9636b7 |
