A New Weight and Sensitivity Based Variable Maximum Distance to Average Vector Algorithm for Wearable Sensor Data Privacy Protection
The problem of privacy protection of wearable devices when publishing data can be solved based on the variable-maximum distance average vector. This paper proposes a new weight and sensitivity based variable maximum distance average vector (WSV-MDAV) method aiming to solve the problems that may be c...
Main Authors: | Zhenjiang Zhang, Bowen Han, Han-Chieh Chao, Feng Sun, Lorna Uden, Di Tang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8756281/ |
Similar Items
-
Effective Privacy-Preserving Collection of Health Data from a User’s Wearable Device
by: Jong Wook Kim, et al.
Published: (2020-09-01) -
A Practical Privacy-Preserving Publishing Mechanism Based on Personalized k-Anonymity and Temporal Differential Privacy for Wearable IoT Applications
by: Junqi Guo, et al.
Published: (2021-06-01) -
Enhancing Privacy in Wearable IoT through a Provenance Architecture
by: Richard K. Lomotey, et al.
Published: (2018-04-01) -
Data Privacy Protection Based on Micro Aggregation with Dynamic Sensitive Attribute Updating
by: Yancheng Shi, et al.
Published: (2018-07-01) -
FacePET: Enhancing Bystanders’ Facial Privacy with Smart Wearables/Internet of Things
by: Alfredo J. Perez, et al.
Published: (2018-12-01)