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DroidClassifier: Efficient Adaptive Mining of Application-Layer Header for Classifying Android Malware [chapter]

Zhiqiang Li, Lichao Sun, Qiben Yan, Witawas Srisa-an, Zhenxiang Chen
2017 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
A recent report has shown that there are more than 5,000 malicious applications created for Android devices each day.  ...  To address this need, we introduce DroidClassifier: a systematic framework for classifying network traffic generated by mobile malware.  ...  Any opinions, findings, conclusions, or recommendations expressed here are those of the authors and do not necessarily reflect the views of the funding agencies or the U.S. Government.  ... 
doi:10.1007/978-3-319-59608-2_33 fatcat:vm6yxskpyzgc5l75e6jxqnjqhu