Achieving privacy preservation in WiFi fingerprint-based localization
Title | Achieving privacy preservation in WiFi fingerprint-based localization |
Publication Type | Conference Paper |
Year of Publication | 2014 |
Authors | Hong Li, Limin Sun, Haojin Zhu, Xiang Lu, Xiuzhen Cheng |
Conference Name | INFOCOM, 2014 Proceedings IEEE |
Date Published | April |
Keywords | Accuracy, Android smartphone, computational overhead reduction, computer network security, cryptography, data privacy, Databases, homomorphic encryption, IEEE 802.11 Standards, indoor localization, indoor mobility prediction, localization service provider, location privacy, mobile computing, performance enhancement algorithm, privacy, privacy-preserving WiFi fingerprint localization scheme, PriWFL, real-world environments, Servers, signal strengths, smart phones, WiFi fingerprint-based localization, wireless LAN |
Abstract | WiFi fingerprint-based localization is regarded as one of the most promising techniques for indoor localization. The location of a to-be-localized client is estimated by mapping the measured fingerprint (WiFi signal strengths) against a database owned by the localization service provider. A common concern of this approach that has never been addressed in literature is that it may leak the client's location information or disclose the service provider's data privacy. In this paper, we first analyze the privacy issues of WiFi fingerprint-based localization and then propose a Privacy-Preserving WiFi Fingerprint Localization scheme (PriWFL) that can protect both the client's location privacy and the service provider's data privacy. To reduce the computational overhead at the client side, we also present a performance enhancement algorithm by exploiting the indoor mobility prediction. Theoretical performance analysis and experimental study are carried out to validate the effectiveness of PriWFL. Our implementation of PriWFL in a typical Android smartphone and experimental results demonstrate the practicality and efficiency of PriWFL in real-world environments. |
DOI | 10.1109/INFOCOM.2014.6848178 |
Citation Key | 6848178 |
- location privacy
- wireless LAN
- WiFi fingerprint-based localization
- smart phones
- signal strengths
- Servers
- real-world environments
- PriWFL
- privacy-preserving WiFi fingerprint localization scheme
- privacy
- performance enhancement algorithm
- mobile computing
- Accuracy
- localization service provider
- indoor mobility prediction
- indoor localization
- IEEE 802.11 Standards
- Homomorphic encryption
- Databases
- data privacy
- Cryptography
- computer network security
- computational overhead reduction
- Android smartphone