DocumentCode :
3316648
Title :
ACComplice: Location inference using accelerometers on smartphones
Author :
Han, Jun ; Owusu, Emmanuel ; Nguyen, Le T. ; Perrig, Adrian ; Zhang, Joy
Author_Institution :
Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
2012
fDate :
3-7 Jan. 2012
Firstpage :
1
Lastpage :
9
Abstract :
The security and privacy risks posed by smartphone sensors such as microphones and cameras have been well documented. However, the importance of accelerometers have been largely ignored. We show that accelerometer readings can be used to infer the trajectory and starting point of an individual who is driving. This raises concerns for two main reasons. First, unauthorized access to an individual´s location is a serious invasion of privacy and security. Second, current smartphone operating systems allow any application to observe accelerometer readings without requiring special privileges. We demonstrate that accelerometers can be used to locate a device owner to within a 200 meter radius of the true location. Our results are comparable to the typical accuracy for handheld global positioning systems.
Keywords :
accelerometers; mobile computing; operating systems (computers); smart phones; telecommunication security; ACComplice; Global Positioning Systems; accelerometers; cameras; location inference; microphones; operating systems; privacy risk; security risk; smartphone sensor; Accelerometers; Dead reckoning; Motion segmentation; Probability; Roads; Sensors; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Systems and Networks (COMSNETS), 2012 Fourth International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4673-0296-8
Electronic_ISBN :
978-1-4673-0297-5
Type :
conf
DOI :
10.1109/COMSNETS.2012.6151305
Filename :
6151305
Link To Document :
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