Abstract
In the last decade, we observed a constantly growing number of Location-Based Services (LBSs) used in indoor environments, such as for targeted advertising in shopping malls or finding nearby friends. Although privacy-preserving LBSs were addressed in the literature, there was a lack of attention to the problem of enhancing privacy of indoor localization, i.e., the process of obtaining the users’ locations indoors and, thus, a prerequisite for any indoor
LBS.
In this work we present PILOT, the first practically efficient solution for Privacy-Preserving Indoor Localization (PPIL) that was obtained by a synergy of the research areas indoor localization and applied cryptography. We design,
implement, and evaluate protocols for Wi-Fi fingerprint-based PPIL that rely on 4 different distance metrics. To save energy and network bandwidth for the mobile end devices in PPIL, we securely outsource the computations to two non-colluding semi-honest parties. Our solution mixes different
secure two-party computation protocols and we design size- and depth-optimized circuits for PPIL. We construct efficient circuit building blocks that are of independent interest: Single Instruction Multiple Data (SIMD) capable oblivious access to an array with low circuit depth and selection of the
k-Nearest Neighbors with small circuit size. Additionally, we reduce Received Signal Strength (RSS) values from 8 bits to 4 bits without any significant accuracy reduction. Our most efficient PPIL protocol is 553x faster than that of Li et al. (INFOCOM’14) and 500x faster than that of Ziegeldorf et al. WiSec’14). Our implementation on commodity hardware has practical run-times of less than 1 second even for the most accurate distance metrics, and it can process more than half a million PPIL queries per day.
LBS.
In this work we present PILOT, the first practically efficient solution for Privacy-Preserving Indoor Localization (PPIL) that was obtained by a synergy of the research areas indoor localization and applied cryptography. We design,
implement, and evaluate protocols for Wi-Fi fingerprint-based PPIL that rely on 4 different distance metrics. To save energy and network bandwidth for the mobile end devices in PPIL, we securely outsource the computations to two non-colluding semi-honest parties. Our solution mixes different
secure two-party computation protocols and we design size- and depth-optimized circuits for PPIL. We construct efficient circuit building blocks that are of independent interest: Single Instruction Multiple Data (SIMD) capable oblivious access to an array with low circuit depth and selection of the
k-Nearest Neighbors with small circuit size. Additionally, we reduce Received Signal Strength (RSS) values from 8 bits to 4 bits without any significant accuracy reduction. Our most efficient PPIL protocol is 553x faster than that of Li et al. (INFOCOM’14) and 500x faster than that of Ziegeldorf et al. WiSec’14). Our implementation on commodity hardware has practical run-times of less than 1 second even for the most accurate distance metrics, and it can process more than half a million PPIL queries per day.
Original language | English |
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Title of host publication | 4th IEEE European Symposium on Security and Privacy (EuroS&P) |
Subtitle of host publication | June 17-19, 2019, Stockholm, Sweden |
Publisher | IEEE |
ISBN (Electronic) | 978-1-7281-1148-3 |
ISBN (Print) | 978-1-7281-1149-0 |
DOIs | |
Publication status | Published - 16 Apr 2019 |
Publication type | A4 Article in conference proceedings |
Event | IEEE European Symposium on Security and Privacy - Duration: 21 Aug 2019 → … |
Conference
Conference | IEEE European Symposium on Security and Privacy |
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Period | 21/08/19 → … |
Publication forum classification
- Publication forum level 1