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A Multidimensional Feature Extraction Method Based on Android Malware Detection

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 494))

Abstract

Due to its unique open source Android system has become a leader in the field of smart phones, allowing researchers to conduct a multi-angle study of the Android system. However, Android system has become malicious code attacks preferred target because of its open source features. For the existing detection scheme in terms of feature extraction due to the selection of too few types of features, the selected features contribute little to the classification accuracy of the classifier is not high and so on. This paper proposes a combination of dynamic and static multidimensional mixed feature extraction scheme, compared with the extraction scheme which only analyzes the authority and the function call, this paper extracts twelve types of features, which reflect the behavior of Android application from multiple perspectives and improve the comprehensiveness of feature extraction.

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Correspondence to Siqing You .

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Xue, F., You, S., Qi, Z., Liu, H. (2019). A Multidimensional Feature Extraction Method Based on Android Malware Detection. In: Sun, S. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2018. Lecture Notes in Electrical Engineering, vol 494. Springer, Singapore. https://doi.org/10.1007/978-981-13-1733-0_1

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  • DOI: https://doi.org/10.1007/978-981-13-1733-0_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1732-3

  • Online ISBN: 978-981-13-1733-0

  • eBook Packages: EngineeringEngineering (R0)

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