Asset Criticality in European Gas Pipeline Systems – Increasing Challenges for NATO, Its Member States and Industrial Protection of Critical Energy Infrastructure

2011 ◽  
pp. 273-303
Author(s):  
Frank Umbach ◽  
Uwe Nerlich
Keyword(s):  
Critical Energy ◽  
Gas Pipeline ◽  
Member States ◽  
Energy Infrastructure ◽  
Pipeline Systems ◽  
Critical Energy Infrastructure

scholarly journals Proactive Critical Energy Infrastructure Protection via Deep Feature Learning

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2622
Author(s):  
Konstantina Fotiadou ◽  
Terpsichori Helen Velivassaki ◽  
Artemis Voulkidis ◽  
Dimitrios Skias ◽  
Corrado De Santis ◽  
...  
Keyword(s):  
Fault Detection ◽  
Wind Turbine ◽  
Short Term Memory ◽  
Feature Learning ◽  
Slight Modification ◽  
Critical Energy ◽  
Normal Operation ◽  
High Detection Rate ◽  
Energy Infrastructure ◽  
Critical Energy Infrastructure

Autonomous fault detection plays a major role in the Critical Energy Infrastructure (CEI) domain, since sensor faults cause irreparable damage and lead to incorrect results on the condition monitoring of Cyber-Physical (CP) systems. This paper focuses on the challenging application of wind turbine (WT) monitoring. Specifically, we propose the two challenging architectures based on learning deep features, namely—Long Short Term Memory-Stacked Autoencoders (LSTM-SAE), and Convolutional Neural Network (CNN-SAE), for semi-supervised fault detection in wind CPs. The internal learnt features will facilitate the classification task by assigning each upcoming measurement into its corresponding faulty/normal operation status. To illustrate the quality of our schemes, their performance is evaluated against real-world’s wind turbine data. From the experimental section we are able to validate that both LSTM-SAE and CNN-SAE schemes provide high classification scores, indicating the high detection rate of the fault level of the wind turbines. Additionally, slight modification on our architectures are able to be applied on different fault/anomaly detection categories on variant Cyber-Physical systems.

Cyber Security and Critical Energy Infrastructure

2014 ◽  
Vol 27 (2) ◽  
pp. 52-60 ◽  
Author(s):  
Ijeoma Onyeji ◽  
Morgan Bazilian ◽  
Chris Bronk
Keyword(s):  
Cyber Security ◽  
Critical Energy ◽  
Energy Infrastructure ◽  
Critical Energy Infrastructure

Towards Fairness-Aware Time-Sensitive Asynchronous Federated Learning for Critical Energy Infrastructure

2021 ◽  
pp. 1-1
Author(s):  
Jianfeng Lu ◽  
Haibo Liu ◽  
Zhao Zhang ◽  
Jiangtao Wang ◽  
Sotirios K. Goudos ◽  
...  
Keyword(s):  
Critical Energy ◽  
Energy Infrastructure ◽  
Critical Energy Infrastructure
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