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ORCIDAndres Robles-Durazno
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Journal Articles
- 2021
[j3]Andres Robles-Durazno, Naghmeh Moradpoor, James McWhinnie, Gordon Russell, Zhiyuan Tan:
Newly engineered energy-based features for supervised anomaly detection in a physical model of a water supply system. Ad Hoc Networks 120: 102590 (2021)- [j2]Andres Robles-Durazno
, Naghmeh Moradpoor, James McWhinnie, Gordon Russell, Jorge Porcel-Bustamante:
Implementation and Evaluation of Physical, Hybrid, and Virtual Testbeds for Cybersecurity Analysis of Industrial Control Systems. Symmetry 13(3): 519 (2021) - 2019
- [j1]Andres Robles-Durazno, Naghmeh Moradpoor, James McWhinnie, Gordon Russell, Inaki Maneru-Marin:
PLC memory attack detection and response in a clean water supply system. Int. J. Crit. Infrastructure Prot. 26 (2019)
Conference and Workshop Papers
- 2023
- [c6]Naghmeh Moradpoor, Leandros Maglaras, Ezra Abah, Andres Robles-Durazno:
The Threat of Adversarial Attacks Against Machine Learning-based Anomaly Detection Approach in a Clean Water Treatment System. DCOSS-IoT 2023: 453-460 - 2022
- [c5]Naghmeh Moradpoor, Masoud Barati, Andres Robles-Durazno, Ezra Abah, James McWhinnie:
Neutralizing Adversarial Machine Learning in Industrial Control Systems Using Blockchain. Cyber Science 2022: 437-451 - 2021
- [c4]Andres Robles-Durazno, Naghmeh Moradpoor, James McWhinnie, Jorge Porcel-Bustamante:
VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems. SIN 2021: 1-7 - 2020
- [c3]Andres Robles-Durazno, Naghmeh Moradpoor, James McWhinnie, Gordon Russell:
Real-time anomaly intrusion detection for a clean water supply system, utilising machine learning with novel energy-based features. IJCNN 2020: 1-8 - 2019
- [c2]Andres Robles-Durazno, Naghmeh Moradpoor, James McWhinnie, Gordon Russell:
WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels*. ICCA 2019: 724-731 - 2018
- [c1]Andres Robles-Durazno, Naghmeh Moradpoor, James McWhinnie, Gordon Russell:
A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system. Cyber Security 2018: 1-8
Coauthor Index
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