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PowerSpy: Location Tracking Using Mobile Device Power Analysis

Yan Michalevsky, Aaron Schulman, Gunaa Arumugam Veerapandian, and Dan Boneh, Stanford University; Gabi Nakibly, National Research and Simulation Center/Rafael Ltd.

Modern mobile platforms like Android enable applications to read aggregate power usage on the phone. This information is considered harmless and reading it requires no user permission or notification. We show that by simply reading the phone’s aggregate power consumption over a period of a few minutes an application can learn information about the user’s location. Aggregate phone power consumption data is extremely noisy due to the multitude of components and applications that simultaneously consume power. Nevertheless, by using machine learning algorithms we are able to successfully infer the phone’s location. We discuss several ways in which this privacy leak can be remedied.

Yan Michalevsky, Stanford University

Aaron Schulman, Stanford University

Gunaa Arumugam Veerapandian, Stanford University

Dan Boneh, Stanford University

Gabi Nakibly, Rafael Ltd.

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BibTeX
@inproceedings {190934,
author = {Yan Michalevsky and Aaron Schulman and Gunaa Arumugam Veerapandian and Dan Boneh and Gabi Nakibly},
title = {{PowerSpy}: Location Tracking Using Mobile Device Power Analysis},
booktitle = {24th USENIX Security Symposium (USENIX Security 15)},
year = {2015},
isbn = {978-1-939133-11-3},
address = {Washington, D.C.},
pages = {785--800},
url = {https://www.usenix.org/conference/usenixsecurity15/technical-sessions/presentation/michalevsky},
publisher = {USENIX Association},
month = aug
}
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