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  • Identifying security challenges_ wind_turbine_ACM_eEnergy

    Rights statement: © ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in e-Energy '19 Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019 http://doi.acm.org/10.1145/3307772.3330154

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Identifying Security Challenges in Renewable Energy Systems: A Wind Turbine Case Study

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

Published
Publication date28/06/2019
Host publicatione-Energy '19 Proceedings of the Tenth ACM International Conference on Future Energy Systems
Place of PublicationNew York
PublisherACM
Pages370-372
Number of pages3
ISBN (Print)9781450366717
Original languageEnglish
EventTenth ACM International Conference on Future Energy Systems (ACM e-Energy) - Phoenix, AZ, United States
Duration: 25/06/201928/06/2019
Conference number: 10
https://energy.acm.org/conferences/eenergy/2019/

Conference

ConferenceTenth ACM International Conference on Future Energy Systems (ACM e-Energy)
Abbreviated titleACM e-Energy 2019
CountryUnited States
CityPhoenix, AZ
Period25/06/1928/06/19
Internet address

Conference

ConferenceTenth ACM International Conference on Future Energy Systems (ACM e-Energy)
Abbreviated titleACM e-Energy 2019
CountryUnited States
CityPhoenix, AZ
Period25/06/1928/06/19
Internet address

Abstract

Distributed renewable energy systems (DRESs) and their interconnection network, typically using Internet-based protocols, are susceptible to a wide range of cybersecurity and resilience challenges. These challenges have been shown to cause problems for the overall grid optimization process. In order to detect such events, we argue that an adequate correlation between network and energy generation data is required. Therefore, in this study, we provide a work-in-progress insight related to the profiling of real network data and energy generation measurements gathered by a local windturbine at Lancaster University. We argue that such an analysis is very important to profile various attack vectors in the modern energy networks that consider DRESs and take necessary actions to prevent any data breaches in the future.

Bibliographic note

© ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in e-Energy '19 Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019 http://doi.acm.org/10.1145/3307772.3330154