CRFeb 5, 2018

PinMe: Tracking a Smartphone User around the World

arXiv:1802.01468v136 citations
Originality Highly original
AI Analysis

This addresses location privacy concerns for smartphone users by demonstrating a novel attack that bypasses previous limitations, potentially impacting security and privacy in mobile computing.

The paper tackles the problem of tracking smartphone users without GPS by introducing PinMe, a mechanism that uses non-sensory/sensory data and public information to estimate location, achieving location estimation even when all location services are disabled.

With the pervasive use of smartphones that sense, collect, and process valuable information about the environment, ensuring location privacy has become one of the most important concerns in the modern age. A few recent research studies discuss the feasibility of processing data gathered by a smartphone to locate the phone's owner, even when the user does not intend to share his location information, e.g., when the Global Positioning System (GPS) is off. Previous research efforts rely on at least one of the two following fundamental requirements, which significantly limit the ability of the adversary: (i) the attacker must accurately know either the user's initial location or the set of routes through which the user travels and/or (ii) the attacker must measure a set of features, e.g., the device's acceleration, for potential routes in advance and construct a training dataset. In this paper, we demonstrate that neither of the above-mentioned requirements is essential for compromising the user's location privacy. We describe PinMe, a novel user-location mechanism that exploits non-sensory/sensory data stored on the smartphone, e.g., the environment's air pressure, along with publicly-available auxiliary information, e.g., elevation maps, to estimate the user's location when all location services, e.g., GPS, are turned off.

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