Abstract
In recent years, smartwatches, which are the most representative wearable device exploiting Internet of things technologies, have been developed and used. With growing use of smartwatches in the healthcare field, there have been considerable efforts to use diverse smartwatch sensor data such as heart rates and body temperatures with the aim of improving healthcare services. However, because the data collected from smartwatches usually contain sensitive user information, individual users are reluctant to provide their data to healthcare service providers because of privacy concerns. Thus, to support such healthcare service provider needs, a method capable of collecting individuals' sensitive data from smartwatches, while preserving privacy, is presented. Preliminary experimental results demonstrate that the proposed approach is well suited to the collection of smartwatch users' sensitive data for the purpose of inferring population statistics while preserving privacy.
Original language | English |
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Title of host publication | 2019 IEEE International Conference on Consumer Electronics, ICCE 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538679104 |
DOIs | |
Publication status | Published - 2019 Mar 6 |
Event | 2019 IEEE International Conference on Consumer Electronics, ICCE 2019 - Las Vegas, United States Duration: 2019 Jan 11 → 2019 Jan 13 |
Publication series
Name | 2019 IEEE International Conference on Consumer Electronics, ICCE 2019 |
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Conference
Conference | 2019 IEEE International Conference on Consumer Electronics, ICCE 2019 |
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Country/Territory | United States |
City | Las Vegas |
Period | 19/1/11 → 19/1/13 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This work was supported in part by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No.2017-0-01703, Wireless Transmission System for Full-Parallax Multiview) and in part by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No.2018-0-00269, A research on safe and convenient big data processing methods).
Publisher Copyright:
© 2019 IEEE.
All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering
- Media Technology
- Electrical and Electronic Engineering