Dr Siamak Layeghy
Lecturer
School of Electrical Engineering and Computer Science
+61 7 336 53775
Researcher biography
Opportunities for Students
I am keen to supervise motivated postgraduate and PhD students who are passionate about AI, cybersecurity, or networking. My research group offers hands-on projects, including developing AI-driven intrusion detection systems, securing IoT ecosystems, and optimising SDN frameworks. Students will gain experience with state-of-the-art ML tools, collaborate with industry partners, and contribute to high-impact publications. Ideal candidates should have strong programming skills (e.g., Python, C++) and a basic understanding of ML or networking concepts, though enthusiasm and a willingness to learn are equally valued.
Why Join My Group?
My research is inherently interdisciplinary, bridging AI, cybersecurity, and networking to address real-world problems. Students will work on cutting-edge projects with access to UQ's world-class facilities and opportunities to collaborate with global experts. Whether you're interested in defending against cyber threats or shaping the future of IoT and SDN, my group provides a dynamic environment to grow as a researcher.
About Me
As a passionate researcher at The University of Queensland, I explore the intersection of Artificial Intelligence (AI) and Machine Learning (ML) with cutting-edge applications in cybersecurity, Internet of Things (IoT), and Software Defined Networking (SDN). My work focuses on developing innovative, real-world solutions to protect digital systems and optimise network performance, mentoring the next generation of researchers to tackle global challenges.
Publications
Book Chapter
Layeghy, Siamak and Portmann, Marius (2022). SCOR: a constraint programming approach to software defined networking. Horizons in computer science research. Volume 22. (pp. 141-191) edited by Thomas S. Clary. New York, NY United States: Nova Science Publishers.
Journal Articles
Manocchio, Liam Daly, Layeghy, Siamak, Gallagher, Marcus and Portmann, Marius (2025). An empirical evaluation of preprocessing methods for machine learning based network intrusion detection systems. Engineering Applications of Artificial Intelligence, 158 111289, 1-16. doi: 10.1016/j.engappai.2025.111289
Sablica, 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
Daly 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, 22 (2), 2120-2137. doi: 10.1109/tnsm.2025.3552844
Dolnicar, 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
Manocchio, 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
Manocchio, 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
Manocchio, 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
Sarhan, 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
Layeghy, 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
Ghosh, 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, PP (99), 1-1. doi: 10.1109/tce.2024.3516498
Hosseininoorbin, 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
Lo, 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
Hosseininoorbin, 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
Hosseininoorbin, 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
Layeghy, 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
Layeghy, 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
Sarhan, 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
Lo, 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
Caville, 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
Sarhan, 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
Sarhan, 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
Sarhan, Mohanad, Lo, Wai Weng, Layeghy, Siamak and Portmann, Marius (2022). HBFL: a hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection. Computers and Electrical Engineering, 103 108379, 1-17. doi: 10.1016/j.compeleceng.2022.108379
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2021). Towards a standard feature set for network intrusion detection system datasets. Mobile Networks and Applications, 27 (1), 357-370. doi: 10.1007/s11036-021-01843-0
Mesbah, Mostefa, Khlif, Mohamed Salah, Layeghy, Siamak, East, Christine E., Dong, Shiying, Brodtmann, Amy, Colditz, Paul B. and Boashash, Boualem (2021). Automatic fetal movement recognition from multi-channel accelerometry data. Computer Methods and Programs in Biomedicine, 210 106377, 106377. doi: 10.1016/j.cmpb.2021.106377
Hosseininoorbin, Seyedehfaezeh, Layeghy, Siamak, Kusy, Brano, Jurdak, Raja, Bishop-Hurley, Greg J., Greenwood, Paul L and Portmann, Marius (2021). Deep learning-based cattle behaviour classification using joint time-frequency data representation. Computers and Electronics in Agriculture, 187 106241, 106241. doi: 10.1016/j.compag.2021.106241
Melis, Andrea, Layeghy, Siamak, Berardi, Davide, Portmann, Marius, Prandini, Marco and Callegati, Franco (2020). P-SCOR: integration of constraint programming orchestration and programmable data plane. IEEE Transactions on Network and Service Management, 18 (1) 9311177, 1-1. doi: 10.1109/tnsm.2020.3048277
Al-Najjar, Anees, Layeghy, Siamak, Portmann, Marius and Indulska, Jadwiga (2018). Flow-level load balancing of HTTP traffic using open flow. Australian Journal of Telecommunications and the Digital Economy, 6 (4), 75-95. doi: 10.18080/ajtde.v6n4.166
Layeghy, Siamak, Pakzad, Farzaneh and Portmann, Marius (2017). A new QoS routing northbound interface for SDN. Australian Journal of Telecommunications and the Digital Economy, 5 (1), 92-115. doi: 10.18080/ajtde.v5n1.91
Odabaee, Maryam, Tokariev, Anton, Layeghy, Siamak, Mesbah, Mostefa, Colditz, Paul B., Ramon, Ceon and Vanhatalo, Sampsa (2014). Neonatal EEG at scalp is focal and implies high skull conductivity in realistic neonatal head models. NeuroImage, 96, 73-80. doi: 10.1016/j.neuroimage.2014.04.007
Conference Papers
Houssel, Paul R. B., Singh, Priyanka, Layeghy, Siamak and Portmann, Marius (2024). Towards Explainable Network Intrusion Detection using Large Language Models. 2024 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Sharjah, United Arab Emirates, 16-19 December 2024. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/bdcat63179.2024.00021
Sarhan, 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
Manocchio, Liam Daly, Layeghy, Siamak and Portmann, Marius (2022). Network intrusion detection system in a light bulb. 32nd International Telecommunication Networks and Applications Conference (ITNAC), Wellington, New Zealand, 30 November- 2 December 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/itnac55475.2022.9998371
Lo, Wai Weng, Layeghy, Siamak, Sarhan, Mohanad, Gallagher, Marcus and Portmann, Marius (2022). Graph neural network-based android malware classification with jumping knowledge. 2022 IEEE Conference on Dependable and Secure Computing (DSC), Edinburgh, United Kingdom, 22-24 June 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/dsc54232.2022.9888878
Lo, 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
Manocchio, Liam Daly, Layeghy, Siamak and Portmann, Marius (2021). FlowGAN - Synthetic Network Flow Generation using Generative Adversarial Networks. International Conference on Computational Science and Engineering (CSE), Shenyang, China, 20-22 October 2021. Piscataway, NJ, United States: IEEE. doi: 10.1109/cse53436.2021.00033
Hosseininoorbin, Seyedehfaezeh, Layeghy, Siamak, Kusy, Brano, Jurdak, Raja and Portmann, Marius (2021). Scaling Spectrogram Data Representation for Deep Learning on Edge TPU. 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Kassel, Germany, 22-26 March 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/PerComWorkshops51409.2021.9431041
Sarhan, 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
Al-Najjar, Anees, Layeghy, Siamak, Portmann, Marius and Indulska, Jadwiga (2019). Enhancing quality of experience of VoIP traffic in SDN based end-hosts. 28th International Telecommunication Networks and Applications Conference, ITNAC 2018, Sydney, NSW Australia, 21-23 November 2018. New York, NY USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ATNAC.2018.8615286
Alharbi, Talal, Layeghy, Siamak and Portmann, Marius (2017). Experimental evaluation of the impact of DoS attacks in SDN. 27th International Telecommunication Networks and Applications Conference (ITNAC), Melbourne, Australia, 22-24 November 2017. Piscataway, NJ, United States: IEEE.
Al-Najjar, Anees, Pakzad, Farzaneh, Layeghy, Siamak and Portmann, Marius (2017). Link capacity estimation in SDN-based end-hosts. 10th International Conference on Signal Processing and Communication Systems, ICSPCS 2016, Surfers Paradise, QLD, Australia, 19 - 21 December 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICSPCS.2016.7843372
Pakzad, Farzaneh, Layeghy, Siamak and Portmann, Marius (2017). Evaluation of Mininet-WiFi integration via ns-3. 26th International Telecommunication Networks and Applications Conference, ITNAC 2016, Dunedin, New Zealand, 7 - 9 December 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ATNAC.2016.7878816
Layeghy, Siamak, Pakzad, Farzaneh and Portmann, Marius (2016). SCOR: constraint programming based northbound interface for SDN. International Telecommunication Networks and Applications Conference, ITNAC, Dunedin, New Zealand, 7-9 December 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/ATNAC.2016.7878788
Al-Najjar, Anees, Layeghy, Siamak and Portmann, Marius (2016). Pushing SDN to the end-host, network load balancing using OpenFlow. 13th IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016, Sydney, NSW, Australia, 14-18 March 2016. NEW YORK: Institute of Electrical and Electronics Engineers. doi: 10.1109/PERCOMW.2016.7457129
Layeghy, Siamak, Azemi, Ghasem, Colditz, Paul and Boashash, Boualem (2014). Non-invasive monitoring of fetal movements using time-frequency features of accelerometry. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), Florence, Italy, 4-9 May 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICASSP.2014.6854429
Layeghy, Siamak, Azemi, Ghasem, Colditz, Paul and Boashash, Boualem (2014). Classification of fetal movement accelerometry through time-frequency features. International Conference on Signal Processing and Communication Systems (ICSPCS), Gold Coast, QLD, Australia, 15-17 December 2014. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICSPCS.2014.7021055
Odabaee, Maryam, Layeghy, Siamak, Mesbah, Mostefa, Azemi, Ghasem, Boashash, Boualem, Colditz, Paul and Vanhatalo, Sampsa (2012). EEG amplitude and correlation spatial decay analysis for neonatal head modelling. 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012, Montreal, QC Canada, 2 - 5 July 2012. Piscataway, NJ United States: I E E E. doi: 10.1109/ISSPA.2012.6310679
Khlif, Mohamed Salah H., Boashash, Boualem, Layeghy, Siamak, Ben-Jabeur, Taoufik, Colditz, Paul B. and East, Christine (2012). A passive DSP approach to fetal movement detection for monitoring fetal health. 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA), Montreal, Canada, 2-5 July 2012. Piscataway, NJ, Australia: IEEE. doi: 10.1109/ISSPA.2012.6310647
Layeghy, S., Odabaee, M., Khlif, M.S. and Amindavar, H.R. (2011). A time frequency approach to CFAR detection. 11th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2011), Bilbao, Spain, 14-17 December 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ISSPIT.2011.6151565
Khlif, M.S., Boashash, B., Layeghy, S., Ben-Jabeur, T., Mesbah, M., East, C. and Colditz, P. (2011). Time-Frequency Characterization of Tri-Axial Accelerometer Data for Fetal Movement Detection. IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Bilbao, Spain, 14-17 December 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ISSPIT.2011.6151607
Thesis
Layeghy, Siamak (2018). SCOR: Software-defined Constrained Optimal Routing Platform for SDN. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/uql.2018.820
Data Collections
Luay, 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
Luay, 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
Luay, 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
Luay, 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
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-UNSW-NB15. The University of Queensland. (Dataset) doi: 10.48610/5d0832d
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-BoT-IoT. The University of Queensland. (Dataset) doi: 10.48610/62e6d80
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-UQ-NIDS. The University of Queensland. (Dataset) doi: 10.48610/69b5a53
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-ToN-IoT. The University of Queensland. (Dataset) doi: 10.48610/2fa2ed6
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-UNSW-NB15-v2. The University of Queensland. (Dataset) doi: 10.48610/ffbb0c1
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-ToN-IoT-v2. The University of Queensland. (Dataset) doi: 10.48610/38a2d07
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). CIC-ToN-IoT. The University of Queensland. (Dataset) doi: 10.48610/f6884ce
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marus (2023). CIC-BoT-IoT. The University of Queensland. (Dataset) doi: 10.48610/c80fccd
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-BoT-IoT-v2. The University of Queensland. (Dataset) doi: 10.48610/ec73920
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-UQ-NIDS-v2. The University of Queensland. (Dataset) doi: 10.48610/631a24a
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-CSE-CIC-IDS2018-v2. The University of Queensland. (Dataset) doi: 10.48610/e9636b7
Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-CSE-CIC-IDS2018. The University of Queensland. (Dataset) doi: 10.48610/b9ed88b