A Privacy Preserving Method for Crowdsourcing in Indoor Fingerprinting Localization

Localization services have gained popularity in recent years to facilitate the daily lives of users. With increasing people desire to use Location Based Services (LBSs), the privacy of users has become critical. Most of these services thus use an anonymizer between Location Service Provider (LSP) an...

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Bibliographic Details
Published in2018 8th International Conference on Computer and Knowledge Engineering (ICCKE) pp. 58 - 62
Main Authors Alikhani, Nasim, Moghtadaiee, Vahideh, Sazdar, Amir Mahdi, Ghorashi, Seyed Ali
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2018
Subjects
Crowdsourcing
Estimation
Fingerprint recognition
Hilbert Curve
Indoor environments
Indoor Localization
LBS
Privacy
Privacy Preserving
Servers
Wireless fidelity
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Summary:Localization services have gained popularity in recent years to facilitate the daily lives of users. With increasing people desire to use Location Based Services (LBSs), the privacy of users has become critical. Most of these services thus use an anonymizer between Location Service Provider (LSP) and the user to protect the user's identity from LSP. One of the localization techniques in indoor environments is Wi-Fi based location fingerprinting which uses received signal strengths (RSSs) at different locations. In this paper, we propose a method to preserve the privacy of users from anonymizer. Hilbert curve and double encryption technique are used. The simulation results indicate that by using the proposed privacy preserving method, the level of privacy preserving is increased.
DOI:10.1109/ICCKE.2018.8566402