Title

Efficient Privacy-Preserving Fingerprint-Based Indoor Localization Using Crowdsourcing

Keywords

Efficiency; fingerprint; localization; privacy; WiFi

Abstract

Indoor localization has been widely studied due to the inability of GPS to function indoors. Numerous approaches have been proposed in the past and a number of these approaches are currently being used commercially. However, little attention was paid to the privacy of the users especially in the commercial products. Malicious individuals can determine a client's daily habits and activities by simply analyzing their WiFi signals and tracking information. In this paper, we implemented a privacy-preserving indoor localization scheme that is based on a fingerprinting approach to analyze the performance issues in terms of accuracy, complexity, scalability and privacy. We developed an Android app and collected a large number of data on the third floor of the FIU Engineering Center. The analysis of data provided excellent opportunities for performance improvement which have been incorporated to the privacy-preserving localization scheme.

Publication Date

12-28-2015

Publication Title

Proceedings - 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015

Number of Pages

549-554

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/MASS.2015.76

Socpus ID

84964662716 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84964662716

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