Overview
Background
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.
Availability
- Dr Siamak Layeghy is:
- Available for supervision
Qualifications
- Doctor of Philosophy, The University of Queensland
Research interests
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AI/ML for Cybersecurity
I develop advanced intrusion detection systems (NIDS and HIDS) using techniques like Transformers, Generative Adversarial Networks (GANs), and Transfer Learning to detect and mitigate cyber threats in real time.
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Edge Learning and IoT Security
My work focuses on lightweight AI models for resource-constrained IoT devices, enabling secure and efficient edge computing.
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Software Defined Networking (SDN)
I explore network optimisation and programmable data planes (e.g., P4) to enhance Quality of Service (QoS) and constrained routing for next-generation networks.
Research impacts
Research Vision
My research leverages AI and ML to secure and optimise emerging technologies. By combining advanced techniques like Large Language Models (LLMs), Graph Neural Networks (GNNs), and Federated Learning with practical applications, I aim to create robust, scalable systems for network security, edge computing, and programmable networks. My goal is to address pressing challenges in cybersecurity and IoT, ensuring safe and efficient digital ecosystems.
My Google Scholar: https://scholar.google.com.au/citations?user=uB6MlpQAAAAJ&hl=en
Works
Search Professor Siamak Layeghy’s works on UQ eSpace
2022
Journal Article
Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-Based Network Intrusion Detection
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
2022
Journal Article
Cyber threat intelligence sharing scheme based on federated learning for network intrusion detection
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
2022
Journal Article
HBFL: a hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection
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
2022
Conference Publication
Graph neural network-based android malware classification with jumping knowledge
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
2022
Book Chapter
SCOR: a constraint programming approach to software defined networking
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.
2021
Journal Article
Towards a standard feature set for network intrusion detection system datasets
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
2021
Conference Publication
FlowGAN - Synthetic Network Flow Generation using Generative Adversarial Networks
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
2021
Journal Article
Deep learning-based cattle behaviour classification using joint time-frequency data representation
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
2021
Journal Article
Automatic fetal movement recognition from multi-channel accelerometry data
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
2021
Conference Publication
Scaling Spectrogram Data Representation for Deep Learning on Edge TPU
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
2020
Journal Article
P-SCOR: integration of constraint programming orchestration and programmable data plane
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
2019
Conference Publication
Enhancing quality of experience of VoIP traffic in SDN based end-hosts
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
2018
Other Outputs
SCOR: Software-defined Constrained Optimal Routing Platform for SDN
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
2018
Journal Article
Flow-level load balancing of HTTP traffic using open flow
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
2017
Journal Article
A new QoS routing northbound interface for SDN
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
2017
Conference Publication
Link capacity estimation in SDN-based end-hosts
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
2017
Conference Publication
Evaluation of Mininet-WiFi integration via ns-3
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
2017
Conference Publication
Experimental evaluation of the impact of DoS attacks in SDN
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.
2016
Conference Publication
SCOR: constraint programming based northbound interface for SDN
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
2016
Conference Publication
Pushing SDN to the end-host, network load balancing using OpenFlow
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
Funding
Current funding
Past funding
Supervision
Availability
- Dr Siamak Layeghy is:
- Available for supervision
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Supervision history
Current supervision
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Doctor Philosophy
Enhancing Cyberbullying Detection in Arabic Social Media through Explainable AI and Natural Language Processing: A Human-Centric Approach
Principal Advisor
Other advisors: Professor Marius Portmann
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Doctor Philosophy
Enhancing the Privacy-Preserving ML techniques with Functional Encryption approach
Principal Advisor
Other advisors: Professor Marius Portmann
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Doctor Philosophy
Machine Learning for Improving Services and Management of Software Defined Networks
Principal Advisor
Other advisors: Professor Marius Portmann
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Doctor Philosophy
eXtended Management Network System (xNMS)
Associate Advisor
Other advisors: Professor Marius Portmann
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Doctor Philosophy
Exploring the Capabilities of LoRaWAN IoT Technology for Multisensor Data Collection and Analysis
Associate Advisor
Other advisors: Professor Sara Dolnicar, Professor Marius Portmann
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Doctor Philosophy
Towards Practical Machine Learning Based Network Intrusion Detection
Associate Advisor
Other advisors: Associate Professor Marcus Gallagher, Professor Marius Portmann
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Doctor Philosophy
Low-energy LoRaWAN-based automatic and continuous measurement of organisational environmental performance.
Associate Advisor
Other advisors: Professor Sara Dolnicar, Professor Marius Portmann
Completed supervision
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2023
Doctor Philosophy
Deep Learning at the Edge: Exploring in-situ Classification in IoT
Associate Advisor
Other advisors: Professor Marius Portmann
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2023
Doctor Philosophy
The Detection of Network Cyber Attacks Using Machine Learning
Associate Advisor
Other advisors: Associate Professor Marcus Gallagher, Professor Marius Portmann
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2023
Master Philosophy
Graph Representation Learning for Cyberattack Detection and Forensics
Associate Advisor
Other advisors: Associate Professor Marcus Gallagher, Professor Marius Portmann
Media
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