A blockchain anonymity solution to prevent location homogeneity attacks. (17th September 2022)

• Record Type: Journal Article
• Authors: Liu, Zhenpeng; Liu, Qiannan; Miao, Dewei; Ren, Lele; Zhao, Yonggang
• Is Part Of: Concurrency and computation. Volume 34:Number 27(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-09-17
• Subjects: blockchain -- distributed k‐anonymity -- homogeneity attack -- incentive mechanism -- location semantics; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.7326
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Location‐based services currently face two critical issues: an insufficient number of anonymous users and the problem of location semantic homogeneity. To prevent location homogeneity attacks, we suggest a blockchain‐based anonymization approach. This scheme introduces blockchain to store the anonymous process of the requesting user and collaborating user as evidence, establishes an incentive mechanism to promote cooperation between the two parties, and then selects users who meet the semantic threshold through the location semantic tree to construct the final anonymous set. The security analysis and simulation experiments demonstrate that the scheme suggested in this article can effectively motivate and constrain each user. The semantic security value is close to the maximum value of 1, preventing homogeneity attacks caused by location semantics and protecting users' location privacy.