Abstract—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
simultaneously consuming power. Nevertheless, we show that by
using machine learning techniques, the phone’s location can be
inferred. We discuss several ways in which this privacy leak can
be remedied.
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
simultaneously consuming power. Nevertheless, we show that by
using machine learning techniques, the phone’s location can be
inferred. We discuss several ways in which this privacy leak can
be remedied.
more here........http://arxiv.org/pdf/1502.03182v1.pdf