Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/13233
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dc.contributor.authorAkgün, Meteen_US
dc.contributor.authorÜstündağ Soykan, Elifen_US
dc.contributor.authorSoykan, Gürkanen_US
dc.date.accessioned2023-03-14T08:44:16Z-
dc.date.available2023-03-14T08:44:16Z-
dc.date.issued2023-
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2023.3237643-
dc.identifier.urihttps://hdl.handle.net/11147/13233-
dc.description.abstractThe increasing transformation from the legacy power grid to the smart grid brings new opportunities and challenges to power system operations. Bidirectional communications between home-area devices and the distribution system empower smart grid functionalities. More granular energy consumption data flows through the grid and enables better smart grid applications. This may also lead to privacy violations since the data can be used to infer the consumer's residential behavior, so-called power signature. Energy utilities mostly aggregate the data, especially if the data is shared with stakeholders for the management of market operations. Although this is a privacy-friendly approach, recent works show that this does not fully protect privacy. On the other hand, some applications, like nonintrusive load monitoring, require disaggregated data. Hence, the challenging problem is to find an efficient way to facilitate smart grid operations without sacrificing privacy. In this paper, we propose a privacy-preserving scheme that leverages consumer privacy without reducing accuracy for smart grid applications like load monitoring. In the proposed scheme, we use a trusted execution environment (TEE) to protect the privacy of the data collected from smart appliances (SAs). The scheme allows customer-oriented smart grid applications as the scheme does not use regular aggregation methods but instead uses customer-oriented aggregation to provide privacy. Hence the accuracy loss stemming from disaggregation is prevented. Our scheme protects the transferred consumption data all the way from SAs to Utility so that possible false data injection attacks on the smart meter that aims to deceive the energy request from the grid are also prevented. We conduct security and game-based privacy analysis under the threat model and provide performance analysis of our implementation. Our results demonstrate that the proposed method overperforms other privacy methods in terms of communication and computation cost. The execution time of aggregation for 10,000 customers, each has 20 SAs is approximately 1 second. The decryption operations performed on the TEE have a linear complexity e.g., 172800 operations take around 1 second while 1728000 operations take around 10 seconds. These results can scale up using cloud or hyper-scalers for real-world applications as our scheme performs offline aggregation.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofIEEE Accessen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectLoad monitoringen_US
dc.subjectPrivacyen_US
dc.subjectSecurityen_US
dc.subjectSmart griden_US
dc.titleA privacy-preserving scheme for smart grid using trusted execution environmenten_US
dc.typeArticleen_US
dc.authorid0000-0003-4088-2784en_US
dc.institutionauthorAkgün, Meteen_US
dc.departmentİzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.wosWOS:000927609800001en_US
dc.identifier.scopus2-s2.0-85147298319en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1109/ACCESS.2023.3237643-
dc.contributor.affiliation01. Izmir Institute of Technologyen_US
dc.contributor.affiliationEricsson Product Securityen_US
dc.contributor.affiliationBahçeşehir Üniversitesien_US
dc.relation.issn2169-3536en_US
dc.description.volume11en_US
dc.description.startpage9182en_US
dc.description.endpage9196en_US
dc.identifier.scopusqualityQ1-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.openairetypeArticle-
item.cerifentitytypePublications-
crisitem.author.dept03.04. Department of Computer Engineering-
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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