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Static and Dynamic Analysis for Android Malware Detection

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Advances in Big Data and Cloud Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 645))

Abstract

In this work, we perform a comparitive study on the behavior of malware and benign applications using its static and dynamic features. In static analysis, the permissions required for an application are considered. But in dynamic, we use a tool called Droidbox. Droidbox is an android sandbox which can monitor some app actions like network activities, file system activities, cryptographic activities, information leakage, etc. Here, we consider these actions as well as dynamic API calls of applications. We propose to implement an android malware detector that can detect an app whether it is malware or not, prior to installation.

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Correspondence to Krishna Sugunan .

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Sugunan, K., Gireesh Kumar, T., Dhanya, K.A. (2018). Static and Dynamic Analysis for Android Malware Detection. In: Rajsingh, E., Veerasamy, J., Alavi, A., Peter, J. (eds) Advances in Big Data and Cloud Computing. Advances in Intelligent Systems and Computing, vol 645. Springer, Singapore. https://doi.org/10.1007/978-981-10-7200-0_13

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  • DOI: https://doi.org/10.1007/978-981-10-7200-0_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7199-7

  • Online ISBN: 978-981-10-7200-0

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