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Android Malware Detection Techniques

EasyChair Preprint no. 3707

18 pagesDate: June 30, 2020


The revolution of smart devices such as smartphones, smart washing machines, smart cars is increasing every year, as these devices are provided connected with the network and provide the online functionality and services available with the lowest cost. In this context, the Android operating system (OS) is very popular due to its openness. It has major stakeholder in the smart devices but has also become an attractive target for cyber-criminals. In this chapter, we present some current methods and results in the research area of Android malware detection and analysis of Android malware. We begin by briefly describing the background of the static, dynamic and hybrid analysis of the Android malware detection techniques which provides a general view of the analysis and detection process to the reader. After that, the most popular framework to detect malware is discussed. Then, the most popular and basic algorithm and techniques are discussed which is mostly an analysis of malware. Finally, some conclusions about Android malware detection techniques.

Keyphrases: Android Malware Detection, deep learning, machine learning, Security

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Rajesh Kumar and Mamoun Alazab},
  title = {Android Malware Detection Techniques},
  howpublished = {EasyChair Preprint no. 3707},

  year = {EasyChair, 2020}}
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