Voice Command Fingerprinting with Locality Sensitive Hashes

Batyr Charyyev, Mehmet Hadi Gunes

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Scopus citations

    Abstract

    Smart home speakers are deployed in millions of homes around the world. These speakers enable users to interact with other IoT devices in the household and provide voice assistance such as telling the weather and reminding appointments. Although smart home speakers facilitate many aspects of our life, security and privacy concerns should be analyzed and addressed. In this paper, we show that an attacker sniffing the network traffic of smart speakers can infer voice commands and compromise the privacy of users. Specifically, we propose a method that utilizes the network traffic of the speakers to fingerprint the voice commands of users without a need for extracting traffic features with machine learning algorithms. We evaluated the proposed method on traffic traces of 100 different voice commands on smart home speakers. Our approach correctly infers 42% of voice commands while machine learning models infer 22% to 34%. We also evaluated the effectiveness of the padding method recommended for preventing voice command fingerprinting and observed that the accuracy of proposed fingerprinting method drops down to 15% and accuracy of machine learning methods ranges from 6% to 15% with traffic padding.

    Original languageEnglish
    Title of host publicationCPSIOTSEC 2020 - Proceedings of the 2020 Joint Workshop on CPS and IoT Security and Privacy
    Pages87-92
    Number of pages6
    ISBN (Electronic)9781450380874
    DOIs
    StatePublished - 9 Nov 2020
    Event2020 Joint Workshop on CPS and IoT Security and Privacy, CPSIOTSEC 2020 - Virtual, Online, United States
    Duration: 9 Nov 2020 → …

    Publication series

    NameCPSIOTSEC 2020 - Proceedings of the 2020 Joint Workshop on CPS and IoT Security and Privacy

    Conference

    Conference2020 Joint Workshop on CPS and IoT Security and Privacy, CPSIOTSEC 2020
    Country/TerritoryUnited States
    CityVirtual, Online
    Period9/11/20 → …

    Keywords

    • locality-sensitive hashing
    • network security
    • privacy
    • traffic fingerprinting

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