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Cyber attacks and faults discrimination in intelligent electronic device-based energy management systems

Ruhul Amin, BM, Hossain, MJ, Anwar, A and Zaman, S 2021, Cyber attacks and faults discrimination in intelligent electronic device-based energy management systems, Electronics, vol. 10, no. 6, pp. 1-15, doi: 10.3390/electronics10060650.

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Title Cyber attacks and faults discrimination in intelligent electronic device-based energy management systems
Author(s) Ruhul Amin, BM
Hossain, MJ
Anwar, AORCID iD for Anwar, A orcid.org/0000-0003-3916-1381
Zaman, S
Journal name Electronics
Volume number 10
Issue number 6
Start page 1
End page 15
Total pages 15
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2021-03-11
ISSN 2079-9292
Keyword(s) intelligent electronic device (IED)
cyber attacks
energy management system (EMS)
false data injection attack (FDIA)
Summary Intelligent electronic devices (IEDs) along with advanced information and communication technology (ICT)-based networks are emerging in the legacy power grid to obtain real-time system states and provide the energy management system (EMS) with wide-area monitoring and advanced control capabilities. Cyber attackers can inject malicious data into the EMS to mislead the state estimation process and disrupt operations or initiate blackouts. A machine learning algorithm (MLA)-based approach is presented in this paper to detect false data injection attacks (FDIAs) in an IED-based EMS. In addition, stealthy construction of FDIAs and their impact on the detection rate of MLAs are analyzed. Furthermore, the impacts of natural disturbances such as faults on the system are considered, and the research work is extended to distinguish between cyber attacks and faults by using state-of-the-art MLAs. In this paper, state-of-the-art MLAs such as Random Forest, OneR, Naive Bayes, SVM, and AdaBoost are used as detection classifiers, and performance parameters such as detection rate, false positive rate, precision, recall, and f-measure are analyzed for different case scenarios on the IEEE benchmark 14-bus system. The experimental results are validated using real-time load flow data from the New York Independent System Operator (NYISO).
Language eng
DOI 10.3390/electronics10060650
Indigenous content off
Field of Research 0906 Electrical and Electronic Engineering
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2021, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30149353

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.