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