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Cyber Attack Detection and Trust Management Toolkit for Defence-Related Microgrids

Authors: Charalampos-Rafail, Medentzidis; Thanasis, Kotsiopoulos; Vasileios, Vellikis; Dimosthenis, Ioannidis; Dimitrios, Tzovaras; Panagiotis, Sarigiannidis;

Cyber Attack Detection and Trust Management Toolkit for Defence-Related Microgrids

Abstract

Part 3: Workshop on Defense Applications of AI – (DAAI 2021); International audience; The rise of microgrids in defence applications, as a greener, more economical and efficient source of energy and the consequential softwarization of networks, has led to the emerge of various cyber-threats. The danger of cyber-attacks in defence microgrid facilities cannot be neglected nor undermined, due to the severe consequences that they can cause. To this end, this paper presents a cyberattack detection and cyber attack severity calculation toolkit, with the aim to provide an end-to-end solution to the cyberattack detection in defense IoT/microgrid systems. Concretely, in this paper are presented and evaluated the SPEAR Visual Analytics AI Engine and the SPEAR Grid Trusted Module (GTM) of the SPEAR H2020 project. The aim of the Visual Analytics AI Engine is to detect malicious action that intend to harm the microgrid and to assist the security engineer of an infrastructure to easily detect abnormalities and submit security events accordingly, while the GTM is responsible to calculate the severity of each security event and to assigns trust values to the affected assets of the system. The accurate detection of cyber-attacks and the efficient reputation management, are assessed with data from a real smart home infrastructure with an installed nanogrid, after applying a 3-stage attack against the MODBUS/TCP protocol used by some of the core nanogrid devices.

Subjects by Vocabulary

Microsoft Academic Graph classification: Visual analytics business.industry Event (computing) Computer science Grid Computer security computer.software_genre Home automation Trust management (information system) Cyber-attack Microgrid business Modbus computer

Keywords

Artificial intelligence, Fuzzy logic, [INFO]Computer Science [cs], Microgrids, Cyber-attack detection

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3. Scikit-fuzzy | skfuzzy v0.2 docs. https://pythonhosted.org/scikitfuzzy/overview.html, (Accessed on 03/24/2021)

4. scikit-learn: machine learning in python | scikit-learn 0.24.1 documentation. https://scikit-learn.org/stable/, (Accessed on 03/29/2021)

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7. Abadi, M., Agarwal, A., Barham, P., et al.: TensorFlow: Large-scale machine learning on heterogeneous systems (2015), https://www.tensor ow.org/, software available from tensor ow.org

8. Beg, O.A., Yadav, A.P., Johnson, T.T., Davoudi, A.: Formal online resiliency monitoring in microgrids. In: 2020 Resilience Week (RWS). pp. 99{105 (2020)

9. Beg, O.A., Nguyen, L.V., Johnson, T.T., Davoudi, A.: Cyber-physical anomaly detection in microgrids using time-frequency logic formalism. IEEE Access 9, 20012{ 20021 (2021)

10. Berardi, U., Tomassoni, E., Khaled, K.: A smart hybrid energy system grid for energy e ciency in remote areas for the army. Energies 13(9), 2279 (2020)

  • BIP!
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Funded by
EC| SPEAR
Project
SPEAR
SPEAR: Secure and PrivatE smArt gRid
  • Funder: European Commission (EC)
  • Project Code: 787011
  • Funding stream: H2020 | RIA
Validated by funder
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