Voice presentation attack detection through text-converted voice command analysis

Il Youp Kwak, Jun Ho Huh, Seung Taek Han, Iljoo Kim, Jiwon Yoon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

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%.

Original languageEnglish
Title of host publicationCHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450359702
DOIs
Publication statusPublished - 2019 May 2
Externally publishedYes
Event2019 CHI Conference on Human Factors in Computing Systems, CHI 2019 - Glasgow, United Kingdom
Duration: 2019 May 42019 May 9

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2019 CHI Conference on Human Factors in Computing Systems, CHI 2019
Country/TerritoryUnited Kingdom
CityGlasgow
Period19/5/419/5/9

Keywords

  • Attack detection
  • Voice assistant security
  • Voice command analysis

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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