GOTCHA: Physical intrusion detection with active acoustic sensing using a smart speaker

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Abstract

Voice Assistants (VAs) in the form of smart speakers such as Amazon Alexa, Google Assistant or Apple Siri are now commonplace. Due to their ubiquitous presence they can be useful as home alarm systems. In this work we present the development and evaluation of a novel physical intrusion detection system GOTCHA based on human presence detection with active acoustic sensing. GOTCHA can execute on simple off-the-shelf smart speaker hardware. Periodic audible chirps are employed to gather data which are then processed by a deep autoencoder trained on the acoustic profile of the empty room. As our evaluation shows, GOTCHA achieves promising results of up to 99.2% for the F1-score. Our experiments show that a person can be detected without fail while the system barely generates false alarms. GOTCHA is a viable alternative to passive sensing solutions for physical intrusion detection.

Original languageEnglish
Title of host publicationSecure IT Systems - 29th Nordic Conference, NordSec 2024, Proceedings
EditorsLeonardo Horn Iwaya, Liina Kamm, Leonardo Martucci, Tobias Pulls
PublisherSpringer Science and Business Media Deutschland GmbH
Pages345-363
Number of pages19
ISBN (Print)9783031790065
DOIs
Publication statusPublished - 29 Jan 2025
Event29th Nordic Conference on Secure IT Systems, NordSec 2024 - Karlstad, Sweden
Duration: 6 Nov 20247 Nov 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15396 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference29th Nordic Conference on Secure IT Systems, NordSec 2024
Country/TerritorySweden
CityKarlstad
Period6/11/247/11/24

Keywords

  • Active acoustic sensing
  • Anomaly detection
  • Autoencoder
  • Deep Learning
  • Machine learning
  • Physical intrusion detection

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