Title :
A Classifier of Malicious Android Applications
Author :
Canfora, Gerardo ; Mercaldo, Francesco ; Visaggio, Corrado Aaron
Author_Institution :
Dept. of Eng., Univ. of Sannio, Benevento, Italy
Abstract :
Malware for smart phones is rapidly spreading out. This paper proposes a method for detecting malware based on three metrics, which evaluate: the occurrences of a specific subset of system calls, a weighted sum of a subset of permissions that the application required, and a set of combinations of permissions. The experimentation carried out suggests that these metrics are promising in detecting malware, but further improvements are needed to increase the quality of detection.
Keywords :
invasive software; mobile computing; pattern classification; smart phones; classifier; malicious Android applications; malware detection; smart phones; system calls; Classification algorithms; Internet; Malware; Measurement; Privacy; Smart phones; android; malware; security; smartphone; usability;
Conference_Titel :
Availability, Reliability and Security (ARES), 2013 Eighth International Conference on
Conference_Location :
Regensburg
DOI :
10.1109/ARES.2013.80