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- W2900569897 abstract "Smartphones are rapidly becoming a necessity in our life's and Android is one of the most popular operating system. Android operating system is widespread in today's smart phone market due to its open source model, its easy functionality and huge number of apps. There is a tendency of app user to trust on Android OS is for securing the data but it has been proved that Android OS is more vulnerable. Malware detection for Android OS has becoming an upcoming research problem of interest. The objective of this article is to investigate about the various attributes involved in malware detection. Further it explores about the malware detection techniques. Existing detection mechanism uses algorithms such as Naïve bayes algorithm, Bayesian algorithm, Hybrid algorithm, Ada grad algorithm and other machine learning algorithms to train the sets and to detect the malware This article concludes with challenges which are not yet addressed." @default.
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- W2900569897 date "2018-07-01" @default.
- W2900569897 modified "2023-09-24" @default.
- W2900569897 title "Investigation of Malware Detection Techniques on Smart Phones" @default.
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- W2900569897 doi "https://doi.org/10.1109/icscan.2018.8541197" @default.
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