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A MADM Location Privacy Protection Method Based on Blockchain

Authors :
Hui Wang
Chengjie Wang
Zihao Shen
Kun Liu
Peiqian Liu
Dengwei Lin
Source :
IEEE Access, Vol 9, Pp 27802-27812 (2021)
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

Location-based services make life easier, but they also involve privacy leakage issues. Many location privacy protection algorithms have been proposed to protect the privacy of users. However, these algorithms are usually based on theoretical data, and there are no actual user data to support studies of location privacy protection. To address this problem, we introduce a credit value, convert credit data from users into credit values using the multiple-attribute decision making (MADM) algorithm, store the credit values and transaction information from the anonymous zone construction process in conjunction with a blockchain, and propose a credit value reward and punishment mechanism that treats anonymous zone construction as a two-party game between the requestor and participant. In this game, a credit value reward and punishment mechanism is used to constrain undesirable behaviors. Through simulation experiments, it is verified that the method can be applied in practical scenarios, effectively constrain undesirable user behaviors, quickly construct anonymous zones, and reduce the probability of user location leakage issues.

Details

Language :
English
ISSN :
21693536
Volume :
9
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.43dc9a382996483e9639cb04033cf316
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2021.3058446