Reference : Automatically Locating Malicious Packages in Piggybacked Android Apps
Scientific congresses, symposiums and conference proceedings : Paper published in a journal
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/30028
Automatically Locating Malicious Packages in Piggybacked Android Apps
English
Li, Li mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Li, Daoyuan mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Bissyande, Tegawendé François D Assise mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Klein, Jacques mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC) >]
Cai, Haipeng [Washington State University]
Lo, David [Singapore Management University]
Le Traon, Yves mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
May-2017
Abstract book of the 4th IEEE/ACM International Conference on Mobile Software Engineering and Systems (MobileSoft 2017)
Yes
No
International
The 4th IEEE/ACM International Conference on Mobile Software Engineering and Systems (MobileSoft 2017)
from 22-05-2017 to 23-05-2017
[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 set of piggybacked apps, we are able to automatically locate the malicious packages from piggybacked Android apps with an accuracy of 83.6% in verifying the top five reported items.
SnT
Researchers ; Professionals ; Students ; General public ; Others
http://hdl.handle.net/10993/30028

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