TY - GEN
T1 - MIGDroid
T2 - 2014 23rd International Conference on Computer Communication and Networks, ICCCN 2014
AU - Hu, Wenjun
AU - Tao, Jing
AU - Ma, Xiaobo
AU - Zhou, Wenyu
AU - Zhao, Shuang
AU - Han, Ting
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/25
Y1 - 2014/9/25
N2 - With the increasing popularity of Android platform, Android malware, especially APP-Repackaging malware wherein the malicious code is injected into legitimate Android applications, is spreading rapidly. This paper proposes a new system named MIGDroid, which leverages method invocation graph based static analysis to detect APP-Repackaging Android malware. The method invocation graph reflects the 'interaction' connections between different methods. Such graph can be naturally exploited to detect APP-Repackaging malware because the connections between injected malicious code and legitimate applications are expected to be weak. Specifically, MIGDroid first constructs method invocation graph on the smali code level, and then divides the method invocation graph into weakly connected sub-graphs. To determine which sub-graph corresponds to the injected malicious code, the threat score is calculated for each sub-graph based on the invoked sensitive APIs, and the subgraphs with higher scores will be more likely to be malicious. Experiment results based on 1,260 Android malware samples in the real world demonstrate the specialty of our system in detecting APP-Repackaging Android malware, thereby well complementing existing static analysis systems (e.g., Androguard) that do not focus on APP-Repackaging Android malware.
AB - With the increasing popularity of Android platform, Android malware, especially APP-Repackaging malware wherein the malicious code is injected into legitimate Android applications, is spreading rapidly. This paper proposes a new system named MIGDroid, which leverages method invocation graph based static analysis to detect APP-Repackaging Android malware. The method invocation graph reflects the 'interaction' connections between different methods. Such graph can be naturally exploited to detect APP-Repackaging malware because the connections between injected malicious code and legitimate applications are expected to be weak. Specifically, MIGDroid first constructs method invocation graph on the smali code level, and then divides the method invocation graph into weakly connected sub-graphs. To determine which sub-graph corresponds to the injected malicious code, the threat score is calculated for each sub-graph based on the invoked sensitive APIs, and the subgraphs with higher scores will be more likely to be malicious. Experiment results based on 1,260 Android malware samples in the real world demonstrate the specialty of our system in detecting APP-Repackaging Android malware, thereby well complementing existing static analysis systems (e.g., Androguard) that do not focus on APP-Repackaging Android malware.
KW - Android
KW - malware
KW - method invocation graph
KW - static analysis
UR - https://www.scopus.com/pages/publications/84908179089
U2 - 10.1109/ICCCN.2014.6911805
DO - 10.1109/ICCCN.2014.6911805
M3 - 会议稿件
AN - SCOPUS:84908179089
T3 - Proceedings - International Conference on Computer Communications and Networks, ICCCN
BT - 2014 23rd International Conference on Computer Communication and Networks, ICCCN Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 August 2014 through 7 August 2014
ER -