A Clustering K-Anonymity Privacy-Preserving Method for Wearable IoT Devices
Joint Authors
Source
Security and Communication Networks
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-28
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Wearable technology is one of the greatest applications of the Internet of Things.
The popularity of wearable devices has led to a massive scale of personal (user-specific) data.
Generally, data holders (manufacturers) of wearable devices are willing to share these data with others to get benefits.
However, significant privacy concerns would arise when sharing the data with the third party in an improper manner.
In this paper, we first propose a specific threat model about the data sharing process of wearable devices’ data.
Then we propose a K-anonymity method based on clustering to preserve privacy of wearable IoT devices’ data and guarantee the usability of the collected data.
Experiment results demonstrate the effectiveness of the proposed method.
American Psychological Association (APA)
Liu, Fang& Li, Tong. 2018. A Clustering K-Anonymity Privacy-Preserving Method for Wearable IoT Devices. Security and Communication Networks،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1214174
Modern Language Association (MLA)
Liu, Fang& Li, Tong. A Clustering K-Anonymity Privacy-Preserving Method for Wearable IoT Devices. Security and Communication Networks No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1214174
American Medical Association (AMA)
Liu, Fang& Li, Tong. A Clustering K-Anonymity Privacy-Preserving Method for Wearable IoT Devices. Security and Communication Networks. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1214174
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214174