Abstract
Apart from the Android apps provided by the official market, apps from unofficial markets and third-party resources are always causing a serious security threat to end-users. Because of the overhead of the network, uploading the app to the server for detection is a time-consuming task. In addition, the uploading process also suffers from the threat of attackers. Consequently, a last line of defense on Android devices is necessary and much-needed. To address these problems, we propose an effective Android malware detection system, leveraging deep learning to provide a real-time secure and fast response environment on Android devices.
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Feng, R., Liu, Y., Lin, S. (2019). A Performance-Sensitive Malware Detection System on Mobile Platform. In: Ait-Ameur, Y., Qin, S. (eds) Formal Methods and Software Engineering. ICFEM 2019. Lecture Notes in Computer Science(), vol 11852. Springer, Cham. https://doi.org/10.1007/978-3-030-32409-4_31
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DOI: https://doi.org/10.1007/978-3-030-32409-4_31
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