Professor Marius Portmann
Professor

Marius Portmann

Email: 
Phone: 
+61 7 336 51636

Background

Prof Portmann is the UQ-Cisco Chair of Network Security at the School of Electrical Engineering and Computer Science (EECS) at The University of Queensland (UQ).

He received his PhD in Electrical Engineering from the Swiss Federal Institute of Technology (ETH) in Zürich in 2003. His research interests include Computer Networks, Cybersecurity, IoT (Internet of Things) and applied AI.

Availability

Professor Marius Portmann is:
Available for supervision

Fields of research

Communications engineering Distributed computing and systems software Engineering

Qualifications

  • Masters (Coursework) of Science, Swiss Federal Institute of Technology ETH Zürich
  • Doctor of Philosophy, Swiss Federal Institute of Technology ETH Zürich

Research interests

  • Cyber Security

    Machine Learning based Intrusion Detection

  • Computer Networks

    IoT Networks, Software Defined Networking (SDN)

  • Blockchain Technology

Search Professor Marius Portmann’s works on UQ eSpace

183 works between 2002 and 2025
All (183) Journal Article (58) Book Chapter (7) Conference Publication (100) Book (1) Other Outputs (17)

41 - 60 of 183 works

2023

Book Chapter

Introduction

Sandhu, Muhammad Moid, Khalifa, Sara, Portmann, Marius and Jurdak, Raja (2023). Introduction. Self-Powered Internet of Things. (pp. 3-12) Cham: Springer International Publishing. doi: 10.1007/978-3-031-27685-9_1

Introduction

2023

Other Outputs

NF-CSE-CIC-IDS2018-v2

Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-CSE-CIC-IDS2018-v2. The University of Queensland. (Dataset) doi: 10.48610/e9636b7

NF-CSE-CIC-IDS2018-v2

2023

Other Outputs

NF-CSE-CIC-IDS2018

Sarhan, Mohanad, Layeghy, Siamak and Portmann, Marius (2023). NF-CSE-CIC-IDS2018. The University of Queensland. (Dataset) doi: 10.48610/b9ed88b

NF-CSE-CIC-IDS2018

2022

Journal Article

Anomal-E: A self-supervised network intrusion detection system based on graph neural networks

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

Anomal-E: A self-supervised network intrusion detection system based on graph neural networks

2022

Conference Publication

Network intrusion detection system in a light bulb

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

Network intrusion detection system in a light bulb

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

Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-Based Network Intrusion Detection

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

Cyber threat intelligence sharing scheme based on federated learning for network intrusion detection

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

HBFL: a hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection

2022

Journal Article

Local reference free in-field calibration of low cost air pollution monitoring sensors

Ghosh, Sushmita, Das, Payali, De, Swades, Chatterjee, Shouri and Portmann, Marius (2022). Local reference free in-field calibration of low cost air pollution monitoring sensors. IEEE Transactions on Instrumentation and Measurement, 71 2517613, 1-13. doi: 10.1109/tim.2022.3203446

Local reference free in-field calibration of low cost air pollution monitoring sensors

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

Graph neural network-based android malware classification with jumping knowledge

Featured

2022

Conference Publication

E-GraphSAGE: a graph neural network based intrusion detection system for IoT

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

E-GraphSAGE: a graph neural network based intrusion detection system for IoT

2022

Conference Publication

FDGATII: Fast Dynamic Graph Attention with Initial Residual and Identity

Kulatilleke, Gayan K., Portmann, Marius, Ko, Ryan and Chandra, Shekhar S. (2022). FDGATII: Fast Dynamic Graph Attention with Initial Residual and Identity. 35th Australasian Joint Conference on Artificial Intelligence: AI 2022, Perth, WA Australia, 5–8 December 2022. Cham, Switzerland: Springer. doi: 10.1007/978-3-031-22695-3_6

FDGATII: Fast Dynamic Graph Attention with Initial Residual and Identity

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.

SCOR: a constraint programming approach to software defined networking

2021

Journal Article

Edge intelligence framework for data-driven dynamic priority sensing and transmission

Ghosh, Sushmita, De, Swades, Chatterjee, Shouri and Portmann, Marius (2021). Edge intelligence framework for data-driven dynamic priority sensing and transmission. IEEE Transactions on Green Communications and Networking, 6 (1), 376-390. doi: 10.1109/TGCN.2021.3136139

Edge intelligence framework for data-driven dynamic priority sensing and transmission

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

Towards a standard feature set for network intrusion detection system datasets

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

FlowGAN - Synthetic Network Flow Generation using Generative Adversarial Networks

2021

Journal Article

Task scheduling for energy harvesting-based IoT: a survey and critical analysis

Sandhu, Muhammad Moid, Khalifa, Sara, Jurdak, Raja and Portmann, Marius (2021). Task scheduling for energy harvesting-based IoT: a survey and critical analysis. IEEE Internet of Things Journal, 8 (18) 9446528, 13825-13848. doi: 10.1109/JIOT.2021.3086186

Task scheduling for energy harvesting-based IoT: a survey and critical analysis

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

Deep learning-based cattle behaviour classification using joint time-frequency data representation

2021

Conference Publication

Learning-based Smart Sensing for Energy-Sustainable WSN

Ghosh, Sushmita, De, Swades, Chatterjee, Shouri and Portmann, Marius (2021). Learning-based Smart Sensing for Energy-Sustainable WSN. doi: 10.1109/icc42927.2021.9500317

Learning-based Smart Sensing for Energy-Sustainable WSN

2021

Journal Article

Learning-based adaptive sensor selection framework for multi-sensing WSN

Ghosh, Sushmita, De, Swades, Chatterjee, Shouri and Portmann, Marius (2021). Learning-based adaptive sensor selection framework for multi-sensing WSN. IEEE Sensors Journal, 21 (12) 9388700, 13551-13563. doi: 10.1109/jsen.2021.3069264

Learning-based adaptive sensor selection framework for multi-sensing WSN

Current funding

  • 2025 - 2027
    Mechanisms of Behaviour Change Theory
    ARC Discovery Projects
    Open grant
  • 2024 - 2025
    Customer electricity usage segmentation based on smart meter data
    Energy Queensland Limited
    Open grant

Past funding

  • 2022 - 2023
    Blockchain-based Event Ticketing System
    Innovation Connections
    Open grant
  • 2021 - 2024
    Reducing plate waste in hotels - which interventions are most effective?
    ARC Linkage Projects
    Open grant
  • 2019
    Machine Learning for Automated Network Anomaly Detection, Cyber Security and Analysis - Phase II
    Innovation Connections
    Open grant
  • 2018 - 2019
    Machine Learning for Automated Network Anomaly detection and Analysis
    Innovation Connections
    Open grant
  • 2018
    Smart Lending
    Commonwealth Bank of Australia
    Open grant
  • 2017 - 2020
    Software Defined Networking for the Internet of Things
    Data 61 - University Collaboration Agreement (DUCA)
    Open grant
  • 2015 - 2016
    Test bed for wide-area software defined networking research (ARC LIEF project administered by The University of New South Wales)
    University of New South Wales
    Open grant
  • 2006 - 2008
    Generic Platform for Peer-to-peer Networks and Applications
    UQ New Staff Research Start-Up Fund
    Open grant

Availability

Professor Marius Portmann is:
Available for supervision

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Supervision history

Current supervision

Completed supervision

Enquiries

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