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Towards reactive acoustic jamming for personal voice assistants

Towards reactive acoustic jamming for personal voice assistants
Towards reactive acoustic jamming for personal voice assistants

Personal Voice Assistants (PVAs) such as the Amazon Echo are commonplace and it is now likely to always be in range of at least one PVA. Although the devices are very helpful they are also continuously monitoring conversations. When a PVA detects a wake word, the immediately following conversation is recorded and transported to a cloud system for further analysis. In this paper we investigate an active protection mechanism against PVAs: reactive jamming. A Protection Jamming Device (PJD) is employed to observe conversations. Upon detection of a PVA wake word the PJD emits an acoustic jamming signal. The PJD must detect the wake word faster than the PVA such that the jamming signal still prevents wake word detection by the PVA. The paper presents an evaluation of the effectiveness of different jamming signals. We quantify the impact of jamming signal and wake word overlap on jamming success. Furthermore, we quantify the jamming false positive rate in dependence of the overlap. Our evaluation shows that a 100% jamming success can be achieved with an overlap of at least 60% with a negligible false positive rate. Thus, reactive jamming of PVAs is feasible without creating a system perceived as a noise nuisance.

Acoustic privacy, Reactive acoustic jamming, Security and privacy in IoT, Wake word detection
1543-7221
12-17
Association for Computing Machinery
Cheng, Peng
1e49aef0-36ef-4cda-af2a-9753881419c9
Bagci, Ibrahim Ethem
e1bbc020-49d6-4201-b40b-b80a049b4c11
Yan, Jeff
a2c03187-3722-46c8-b73b-439eb9d1a10e
Roedig, Utz
77ec02bf-0a48-4960-b02a-892f27501e6d
Cheng, Peng
1e49aef0-36ef-4cda-af2a-9753881419c9
Bagci, Ibrahim Ethem
e1bbc020-49d6-4201-b40b-b80a049b4c11
Yan, Jeff
a2c03187-3722-46c8-b73b-439eb9d1a10e
Roedig, Utz
77ec02bf-0a48-4960-b02a-892f27501e6d

Cheng, Peng, Bagci, Ibrahim Ethem, Yan, Jeff and Roedig, Utz (2018) Towards reactive acoustic jamming for personal voice assistants. In MPS 2018 - Proceedings of the 2nd International Workshop on Multimedia Privacy and Security, co-located with CCS 2018. Association for Computing Machinery. pp. 12-17 . (doi:10.1145/3267357.3267359).

Record type: Conference or Workshop Item (Paper)

Abstract

Personal Voice Assistants (PVAs) such as the Amazon Echo are commonplace and it is now likely to always be in range of at least one PVA. Although the devices are very helpful they are also continuously monitoring conversations. When a PVA detects a wake word, the immediately following conversation is recorded and transported to a cloud system for further analysis. In this paper we investigate an active protection mechanism against PVAs: reactive jamming. A Protection Jamming Device (PJD) is employed to observe conversations. Upon detection of a PVA wake word the PJD emits an acoustic jamming signal. The PJD must detect the wake word faster than the PVA such that the jamming signal still prevents wake word detection by the PVA. The paper presents an evaluation of the effectiveness of different jamming signals. We quantify the impact of jamming signal and wake word overlap on jamming success. Furthermore, we quantify the jamming false positive rate in dependence of the overlap. Our evaluation shows that a 100% jamming success can be achieved with an overlap of at least 60% with a negligible false positive rate. Thus, reactive jamming of PVAs is feasible without creating a system perceived as a noise nuisance.

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More information

Published date: 15 October 2018
Additional Information: Publisher Copyright: © 2018 Association for Computing Machinery.
Venue - Dates: 2nd International Workshop on Multimedia Privacy and Security, MPS 2010, co-located with CCS 2018, , Toronto, Canada, 2018-10-15
Keywords: Acoustic privacy, Reactive acoustic jamming, Security and privacy in IoT, Wake word detection

Identifiers

Local EPrints ID: 500868
URI: http://eprints.soton.ac.uk/id/eprint/500868
ISSN: 1543-7221
PURE UUID: a4940bcd-6009-4e9b-b069-a82e8fc78317

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Date deposited: 14 May 2025 16:51
Last modified: 14 May 2025 16:51

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Contributors

Author: Peng Cheng
Author: Ibrahim Ethem Bagci
Author: Jeff Yan
Author: Utz Roedig

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