Voice presentation attack detection through text-converted voice command analysis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwak, I.-Y. | - |
dc.contributor.author | Huh, J.H. | - |
dc.contributor.author | Han, S.T. | - |
dc.contributor.author | Kim, I. | - |
dc.contributor.author | Yoon, J. | - |
dc.date.accessioned | 2023-03-08T15:44:00Z | - |
dc.date.available | 2023-03-08T15:44:00Z | - |
dc.date.issued | 2019 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/63793 | - |
dc.description.abstract | Voice assistants are quickly being upgraded to support advanced, security-critical commands such as unlocking devices, checking emails, and making payments. In this paper, we explore the feasibility of using users’ text-converted voice command utterances as classification features to help identify users’ genuine commands, and detect suspicious commands. To maintain high detection accuracy, our approach starts with a globally trained attack detection model (immediately available for new users), and gradually switches to a user-specific model tailored to the utterance patterns of a target user. To evaluate accuracy, we used a real-world voice assistant dataset consisting of about 34.6 million voice commands collected from 2.6 million users. Our evaluation results show that this approach is capable of achieving about 3.4% equal error rate (EER), detecting 95.7% of attacks when an optimal threshold value is used. As for those who frequently use security-critical (attack-like) commands, we still achieve EER below 5%. © 2019 Association for Computing Machinery. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Association for Computing Machinery | - |
dc.title | Voice presentation attack detection through text-converted voice command analysis | - |
dc.type | Article | - |
dc.identifier.doi | 10.1145/3290605.3300828 | - |
dc.identifier.bibliographicCitation | Conference on Human Factors in Computing Systems - Proceedings | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000474467907055 | - |
dc.identifier.scopusid | 2-s2.0-85067622621 | - |
dc.citation.title | Conference on Human Factors in Computing Systems - Proceedings | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordAuthor | Attack detection | - |
dc.subject.keywordAuthor | Voice assistant security | - |
dc.subject.keywordAuthor | Voice command analysis | - |
dc.subject.keywordPlus | SPEAKER IDENTIFICATION | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Cybernetics | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.description.journalRegisteredClass | scopus | - |
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