A review of non-technical loss attack models and detection methods in the smart grid

Simple item page
dc.contributor.authorChuwa, Maria Gabriel
dc.contributor.authorWang, Fei
dc.date.accessioned2023-10-12T13:47:42Z
dc.date.available2023-10-12T13:47:42Z
dc.date.issued2021
dc.descriptionAbstract. Full text article available at https://doi.org/10.1016/j.epsr.2021.107415en_US
dc.description.abstractThe advanced metering infrastructure is a key building block for the smart grid, which is responsible for facilitating communication between the smart meter and the electricity provider. However, the development of advanced metering infrastructure leads to more sophisticated attacks that can be launched on the network and have a tremendous effect on the grid. Non-technical losses are the number one and most critical issue contributing to financial losses on smart grids. This paper, therefore, discusses the types and causes of attacks that trigger non-technical losses in the advanced metering infrastructure system and analyzes attacks that result from non-technical losses attack models. This paper also addresses various features and feature-engineering methods and their ability to create distinct classes between normal and attack samples. This study further examines the performances of different learning models in the detection of different types of attacks. Finally, the paper provides a summary and suggestions for further improvement in the detection of non-technical loss attacks.en_US
dc.identifier.citationChuwa, M. G., & Wang, F. (2021). A review of non-technical loss attack models and detection methods in the smart grid. Electric Power Systems Research, 199, 107415.en_US
dc.identifier.otherDOI: https://doi.org/10.1016/j.epsr.2021.107415
dc.identifier.otherURL: https://www.sciencedirect.com/science/article/pii/S0378779621003965?via%3Dihub
dc.identifier.urihttp://hdl.handle.net/20.500.12661/4182
dc.language.isoenen_US
dc.publisherELSEVIERen_US
dc.subjectAMIen_US
dc.subjectAttack modelsen_US
dc.subjectEnergy theften_US
dc.subjectDetectionen_US
dc.subjectNon-technical lossesen_US
dc.subjectSmart griden_US
dc.titleA review of non-technical loss attack models and detection methods in the smart griden_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Christina Muro, Maria Gabriel (2016). review.pdf
Size:
29.92 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Journal Articles