Privacy Leakage in Smart Homes and Its Mitigation: IFTTT as a Case Study

Rixin Xu, Qiang Zeng, Liehuang Zhu, Haotian Chi, Xiaojiang Du

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

1 Citation (Scopus)

Abstract

The combination of an appified smart home platform and third-party apps have enabled developers to contribute their novel ideas to bring more convenience to their users. However, this also brings the potential of privacy leakage. If a third-party app is permitted to monitor a user day and night, then it will learn the behavior pattern of this user before long. In this paper, we exploited how IFTTT monitors the daily life of a user in several ways that are hardly noticeable. We propose the 'Specific-fuzzification' to protect the privacy of a user in two steps: filter the unnecessary events to the IFTTT, then fuzz the value of the events that must be uploaded. We evaluated the 'Specific-fuzzification' on event records of seven users, the result showed comparing the original IFTTT, the modified IFTTT patched with 'Specific-fuzzification' only gained rare events and thus could no longer recognize any behavior patterns of a user.

Original languageEnglish
Title of host publication2018 IEEE 37th International Performance Computing and Communications Conference, IPCCC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538668085
DOIs
Publication statusPublished - 2 Jul 2018
Event37th IEEE International Performance Computing and Communications Conference, IPCCC 2018 - Orlando, United States
Duration: 17 Nov 201819 Nov 2018

Publication series

Name2018 IEEE 37th International Performance Computing and Communications Conference, IPCCC 2018

Conference

Conference37th IEEE International Performance Computing and Communications Conference, IPCCC 2018
Country/TerritoryUnited States
CityOrlando
Period17/11/1819/11/18

Keywords

  • IFTTT
  • SmartThings
  • privacy leakage
  • smart home

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