Adversary Models for Mobile Device Authentication

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorMayrhofer, Renéen_US
dc.contributor.authorSigg, Stephanen_US
dc.contributor.departmentDepartment of Communications and Networkingen
dc.contributor.groupauthorAmbient Intelligenceen
dc.contributor.organizationJohannes Kepler University Linzen_US
dc.date.accessioned2021-12-31T13:59:34Z
dc.date.available2021-12-31T13:59:34Z
dc.date.issued2022-12en_US
dc.descriptionPublisher Copyright: © 2021 Copyright held by the owner/author(s).
dc.description.abstractMobile device authentication has been a highly active research topic for over 10 years, with a vast range of methods proposed and analyzed. In related areas, such as secure channel protocols, remote authentication, or desktop user authentication, strong, systematic, and increasingly formal threat models have been established and are used to qualitatively compare different methods. However, the analysis of mobile device authentication is often based on weak adversary models, suggesting overly optimistic results on their respective security. In this article, we introduce a new classification of adversaries to better analyze and compare mobile device authentication methods. We apply this classification to a systematic literature survey. The survey shows that security is still an afterthought and that most proposed protocols lack a comprehensive security analysis. The proposed classification of adversaries provides a strong and practical adversary model that offers a comparable and transparent classification of security properties in mobile device authentication.en
dc.description.versionPeer revieweden
dc.format.extent35
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationMayrhofer, R & Sigg, S 2022, 'Adversary Models for Mobile Device Authentication', ACM Computing Surveys, vol. 54, no. 9, 198, pp. 1-35. https://doi.org/10.1145/3477601en
dc.identifier.doi10.1145/3477601en_US
dc.identifier.issn0360-0300
dc.identifier.issn1557-7341
dc.identifier.otherPURE UUID: c43a1b5c-d117-40fd-a212-5884ef8cff94en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/c43a1b5c-d117-40fd-a212-5884ef8cff94en_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/77341278/ELEC_Mayrhofer_etal_Adversary_Models_for_Mobile_ACM_Computing_Surveys_2022.pdf
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/112040
dc.identifier.urnURN:NBN:fi:aalto-2021123111180
dc.language.isoenen
dc.publisherACM
dc.relation.ispartofseriesACM Computing Surveysen
dc.relation.ispartofseriesVolume 54, issue 9, pp. 1-35en
dc.rightsopenAccessen
dc.subject.keywordadversary modelen_US
dc.subject.keywordMobile device authenticationen_US
dc.subject.keywordsurveyen_US
dc.titleAdversary Models for Mobile Device Authenticationen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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