[en] To devise efficient approaches and tools for detecting malicious packages in the Android ecosystem, researchers are increasingly required to have a deep understanding of malware. There is thus a need to provide a framework for dissecting malware and locating malicious program fragments within app code in order to build a comprehensive dataset of malicious samples. Towards addressing this need, we propose in this work a tool-based approach called HookRanker, which provides ranked lists of potentially malicious packages based on the way malware behaviour code is triggered. With experiments on a ground truth of piggybacked apps, we are able to automatically locate the malicious packages from piggybacked Android apps with an accuracy@5 of 83.6% for such packages that are triggered through method invocations and an accuracy@5 of 82.2% for such packages that are triggered independently.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
LI, Li ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
LI, Daoyuan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
KLEIN, Jacques ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
Cai, Haipeng; Washington State University > School of Electrical Engineering and Computer Science
Lo, David; Singapore Management University > School of Information Systems
LE TRAON, Yves ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
On Locating Malicious Code in Piggybacked Android Apps