Titlebook: Android Malware Detection using Machine Learning; Data-Driven Fingerpr ElMouatez Billah Karbab,Mourad Debbabi,Djedjiga Mo Book 2021 The Edi

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E. Frey,K. Kroy,J. Wilhelm,E. Sackmann apps packaging structure, which contains not only the actual compiled code but also other content such as media files. To overcome this limitation, we propose an effective and broad fuzzy fingerprint that captures not only binary features but also the underneath structure and semantics of the . package.

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https://doi.org/10.1007/978-3-540-76376-5rtificial neural network that takes, as input, the raw sequences of API method calls, as they appear in the DEX file, to enable malware detection and family attribution. . can automatically recognize malicious patterns using only the sequences of raw method calls in the assembly code.

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Portable Supervised Malware Fingerprinting Using Deep Learning,rtificial neural network that takes, as input, the raw sequences of API method calls, as they appear in the DEX file, to enable malware detection and family attribution. . can automatically recognize malicious patterns using only the sequences of raw method calls in the assembly code.

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Complex Analysis. Kentucky 1976978-3-540-37303-2Series ISSN 0075-8434 Series E-ISSN 1617-9692