Personal Voice Assistant wake word jamming
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Accepted Version
Date
2024-04-23
Authors
Sagi, Prathyusha
Sankar, Arun
Roedig, Utz
Journal Title
Journal ISSN
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Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published Version
Abstract
Personal Voice Assistants (PVAs) such as Apple’s Siri, Amazon’s Alexa and Google Home are now ubiquitous. These devices continuously listen for a wake word that users speak to start interaction with the device. If this wake word recognition is disrupted, the device is not usable anymore. The wake word detection can be impeded by acoustic interference. Interference might be noise (e.g. background music, chatter, engine sounds) or a deliberate acoustic jamming signal. While wake word recognition algorithms might be designed with resilience against noise in mind they are usually not prepared to handle an attacker using a jamming signal. This work provides the first detailed study of acoustic Denial of Service (DoS) jamming attacks on the PVA wake word detection. We describe how a jamming signal should be designed such that wake word detection is jeopardised effectively while minimising jamming effort and jamming detectability. We study the impact of various noise features such as signal type, strength, timing, duration, frequency and bandwidth. Our work shows that accurately timed signals with a very short duration of only 2ms can prevent PVA operations reliably
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Keywords
Pervasive computing , Conferences , Noise , Personal voice assistants , Interference , Acoustics , Timing
Citation
Sagi, P., Sankar, A. and Roedig, U. (2024) 'Personal Voice Assistant wake word jamming', 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Biarritz, France, 11-15 March 2024, pp. 19-24. https://doi.org/10.1109/PerComWorkshops59983.2024.10503529
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© 2024, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.