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

Rixin Xu; Qiang Zeng; Liehuang Zhu; Haotian Chi; Xiaojiang Du; Mohsen Guizani

doi:10.1109/ACCESS.2019.2911202

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

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

Department of Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

42 Scopus citations

Abstract

The combination of smart home platforms and automation apps introduce many conveniences to smart home users. However, this also brings the potential of privacy leakage. If a smart home platform is permitted to collect all the events of a user day and night, then the platform will learn the behavior patterns of this user before long. In this paper, we investigate how IFTTT, one of the most popular smart home platforms, has the capability of monitoring the daily life of a user in a variety of ways that are hardly noticeable. Moreover, we propose multiple ideas for mitigating privacy leakages, which all together form a 'Filter-and-Fuzz' (FF) process: first, it filters out events unneeded by the IFTTT platform. Then, it fuzzifies the values and frequencies of the remaining events. We evaluate the FF process and the results show that the proposed solution makes the IFTTT unable to recognize any of the user's behavior patterns.

Original language	English
Article number	8704324
Pages (from-to)	63457-63471
Number of pages	15
Journal	IEEE Access
Volume	7
DOIs	https://doi.org/10.1109/ACCESS.2019.2911202
State	Published - 2019

Keywords

IFTTT
SmartThings
privacy leakage
smart home

Access to Document

10.1109/ACCESS.2019.2911202

Cite this

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title = "Privacy Leakage in Smart Homes and Its Mitigation: IFTTT as a Case Study",

abstract = "The combination of smart home platforms and automation apps introduce many conveniences to smart home users. However, this also brings the potential of privacy leakage. If a smart home platform is permitted to collect all the events of a user day and night, then the platform will learn the behavior patterns of this user before long. In this paper, we investigate how IFTTT, one of the most popular smart home platforms, has the capability of monitoring the daily life of a user in a variety of ways that are hardly noticeable. Moreover, we propose multiple ideas for mitigating privacy leakages, which all together form a 'Filter-and-Fuzz' (FF) process: first, it filters out events unneeded by the IFTTT platform. Then, it fuzzifies the values and frequencies of the remaining events. We evaluate the FF process and the results show that the proposed solution makes the IFTTT unable to recognize any of the user's behavior patterns.",

keywords = "IFTTT, SmartThings, privacy leakage, smart home",

author = "Rixin Xu and Qiang Zeng and Liehuang Zhu and Haotian Chi and Xiaojiang Du and Mohsen Guizani",

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AU - Xu, Rixin

AU - Zeng, Qiang

AU - Zhu, Liehuang

AU - Chi, Haotian

AU - Du, Xiaojiang

AU - Guizani, Mohsen

PY - 2019

Y1 - 2019

N2 - The combination of smart home platforms and automation apps introduce many conveniences to smart home users. However, this also brings the potential of privacy leakage. If a smart home platform is permitted to collect all the events of a user day and night, then the platform will learn the behavior patterns of this user before long. In this paper, we investigate how IFTTT, one of the most popular smart home platforms, has the capability of monitoring the daily life of a user in a variety of ways that are hardly noticeable. Moreover, we propose multiple ideas for mitigating privacy leakages, which all together form a 'Filter-and-Fuzz' (FF) process: first, it filters out events unneeded by the IFTTT platform. Then, it fuzzifies the values and frequencies of the remaining events. We evaluate the FF process and the results show that the proposed solution makes the IFTTT unable to recognize any of the user's behavior patterns.

AB - The combination of smart home platforms and automation apps introduce many conveniences to smart home users. However, this also brings the potential of privacy leakage. If a smart home platform is permitted to collect all the events of a user day and night, then the platform will learn the behavior patterns of this user before long. In this paper, we investigate how IFTTT, one of the most popular smart home platforms, has the capability of monitoring the daily life of a user in a variety of ways that are hardly noticeable. Moreover, we propose multiple ideas for mitigating privacy leakages, which all together form a 'Filter-and-Fuzz' (FF) process: first, it filters out events unneeded by the IFTTT platform. Then, it fuzzifies the values and frequencies of the remaining events. We evaluate the FF process and the results show that the proposed solution makes the IFTTT unable to recognize any of the user's behavior patterns.

KW - IFTTT

KW - SmartThings

KW - privacy leakage

KW - smart home

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

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Keywords

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