Abstract

Due to the rapid advancement of mobile communication technology,
mobile devices nowadays can support a variety of data services that
are not traditionally available. With the growing
popularity of mobile devices in the last few years, attacks targeting
them are also surging. Existing mobile malware detection techniques,
which are often borrowed from solutions to Internet malware detection,
do not perform as effectively due to the limited computing resources
on mobile devices.

In this work, we propose VirusMeter, a novel and general malware
detection method, to detect anomalous behaviors on mobile devices. The
rationale underlying VirusMeter is the fact that mobile devices are
usually battery powered and any malicious activity would inevitably
consume some battery power. By monitoring power consumption on a
mobile device, VirusMeter catches misbehaviors that lead to abnormal
power consumption. For this purpose, VirusMeter relies on a concise
user-centric power model that characterizes power consumption of
common user behaviors. In a real-time mode, VirusMeter can perform
fast malware detection with trivial runtime overhead. 


Speaker Bio

Lei Liu is a Ph.D. student in Computer Science Department of George
Mason Univesity. His research interests incude system security,
network application, operation systems and sogrware engineering.
Before pursuing his Ph.D. degree, he has several years' experience in
IT industry.