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PlaceRaider: Virtual theft in physical spaces with smartphones (2013)
| Venue: | in Network and Distributed System Security Symposium |
| Citations: | 16 - 3 self |
BibTeX
@INPROCEEDINGS{Templeman13placeraider:virtual,
author = {Robert Templeman and Zahid Rahman and David Cr and Apu Kapadia},
title = {PlaceRaider: Virtual theft in physical spaces with smartphones},
booktitle = {in Network and Distributed System Security Symposium},
year = {2013}
}
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Abstract
Abstract—Each new generation of smartphone features in-creasingly powerful onboard sensor suites. A new strain of ‘sensory malware ’ has been developing that leverages these sensors to steal information from the physical environment — e.g., researchers have recently demonstrated how malware can ‘listen ’ for spoken credit card numbers through the micro-phone, or ‘feel ’ keystroke vibrations using the accelerometer. Yet the possibilities of what malware can ‘see ’ through a camera have been understudied. This paper introduces PlaceRaider, a novel ‘visual malware’ that allows remote attackers to engage in remote reconnais-sance and what we call “virtual theft. ” Through completely opportunistic use of the phone’s camera and other sensors, PlaceRaider constructs rich, three dimensional models of indoor environments. Remote burglars can thus ‘download’ the physical space, study the environment carefully, and steal virtual objects from the environment (such as financial doc-uments, information on computer monitors, and personally identifiable information). Through two human subject studies we demonstrate the effectiveness of using mobile devices as powerful surveillance and virtual theft platforms, and we suggest several possible defenses against visual malware. I.
Keyphrases
virtual theft physical space virtual theft platform new generation remote burglar phone camera keystroke vibration steal virtual object computer monitor powerful surveillance remote reconnais-sance identifiable information visual malware several possible defense opportunistic use new strain physical environment sensor suite sensory malware financial doc-uments dimensional model novel visual malware indoor environment mobile device smartphone feature spoken credit card number human subject study
