Postgraduate research students

Martin Nahalka

Email: m.nahalka.1@research.gla.ac.uk

ORCID iDhttps://orcid.org/0009-0002-9606-5003

Research title: Machine-learning based cyber resilience for the CNI

Research summary

My research focuses on Intrusion Detection and Explainability of attacks, with a particular focus on normal profiling of complex cyber-physical systems (CPS). 

I am particularly interested in the following topics:

  • Provenance-based Intrusion Detection
  • Graph-based neural networks
  • Heterogenous data fusion

Publications

List by: Type | Date

Jump to: 2026 | 2024
Number of items: 2.

2026

Nahalka, Martin, Cook, Marco ORCID logoORCID: https://orcid.org/0000-0002-5232-2381 and Pezaros, Dimitrios ORCID logoORCID: https://orcid.org/0000-0003-0939-378X (2026) Heterogeneous Graph Fusion for Multi-Modal Industrial Anomaly Detection. In: 2026 IEEE International Conference on Cyber Security and Resilience (IEEE CSR), Lisbon, Portugal, 3-5 Aug 2026, (Accepted for Publication)

2024

Nahalka, Martin, Cook, Marco M. ORCID logoORCID: https://orcid.org/0000-0002-5232-2381 and Pezaros, Dimitrios ORCID logoORCID: https://orcid.org/0000-0003-0939-378X (2024) The Good, the Bad and the Ugly: Investigating the Effectiveness of Graph Deep Neural Networks for Anomaly Detection in Industrial Control Systems. In: IFIP International Internet of things (IoT) Conference, Nice, France, 6-8 November 2024, pp. 21-36. ISBN 9783031819001 (doi: 10.1007/978-3-031-81900-1_2)

This list was generated on Wed May 13 14:39:58 2026 BST.
Jump to: Conference Proceedings
Number of items: 2.

Conference Proceedings

Nahalka, Martin, Cook, Marco ORCID logoORCID: https://orcid.org/0000-0002-5232-2381 and Pezaros, Dimitrios ORCID logoORCID: https://orcid.org/0000-0003-0939-378X (2026) Heterogeneous Graph Fusion for Multi-Modal Industrial Anomaly Detection. In: 2026 IEEE International Conference on Cyber Security and Resilience (IEEE CSR), Lisbon, Portugal, 3-5 Aug 2026, (Accepted for Publication)

Nahalka, Martin, Cook, Marco M. ORCID logoORCID: https://orcid.org/0000-0002-5232-2381 and Pezaros, Dimitrios ORCID logoORCID: https://orcid.org/0000-0003-0939-378X (2024) The Good, the Bad and the Ugly: Investigating the Effectiveness of Graph Deep Neural Networks for Anomaly Detection in Industrial Control Systems. In: IFIP International Internet of things (IoT) Conference, Nice, France, 6-8 November 2024, pp. 21-36. ISBN 9783031819001 (doi: 10.1007/978-3-031-81900-1_2)

This list was generated on Wed May 13 14:39:58 2026 BST.

Supervisors