A Non-Intrusive Method for Smart Speaker Forensics

Li Lin, Xuanyu Liu, Xiao Fu, Bin Luo, Xiaojiang Du, Mohsen Guizani

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

8 Scopus citations

Abstract

With the rapid development of the Internet of Things technology, smart speakers have become increasingly popular. However, smart speaker security is an ensuing threat. At present, smart speakers are activated by voice, and they monitor users' voices 24 hours per day. Consequently, there may be problems with user privacy leakage. In this paper, we propose a non-intrusive digital forensic method for smart speakers. The main contribution of the paper is an effective method of combining network traffic analysis with the extraction of user intent and alarms about abnormal network traffic to support the investigation of security. We use Xiaomi smart speakers as an example in an experiment to verify our forensic method. The evaluation results show that our method works well for detecting security risks.

Original languageEnglish
Title of host publicationICC 2021 - IEEE International Conference on Communications, Proceedings
ISBN (Electronic)9781728171227
DOIs
StatePublished - Jun 2021
Event2021 IEEE International Conference on Communications, ICC 2021 - Virtual, Online, Canada
Duration: 14 Jun 202123 Jun 2021

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607

Conference

Conference2021 IEEE International Conference on Communications, ICC 2021
Country/TerritoryCanada
CityVirtual, Online
Period14/06/2123/06/21

Keywords

  • digital forensics
  • network traffic
  • non-intrusive
  • smart speaker
  • users intent

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