Abstract
The usage of mobile phones has increased in our lives because they offer nearly the same functionality as a personal computer. Specifically, Android is one of the most widespread mobile operating systems. Indeed, its app store is one of the most visited and the number of applications available for this platform has also increased. However, as it happens with any popular service, it is prone to misuse, and the number of malware samples has increased dramatically in the last months. Thus, we propose a new method based on anomaly detection that extracts the strings contained in application files in order to detect malware.
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Sanz, B., Santos, I., Ugarte-Pedrero, X., Laorden, C., Nieves, J., Bringas, P.G. (2014). Anomaly Detection Using String Analysis for Android Malware Detection. In: Herrero, Á., et al. International Joint Conference SOCO’13-CISIS’13-ICEUTE’13. Advances in Intelligent Systems and Computing, vol 239. Springer, Cham. https://doi.org/10.1007/978-3-319-01854-6_48
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DOI: https://doi.org/10.1007/978-3-319-01854-6_48
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01853-9
Online ISBN: 978-3-319-01854-6
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