In this paper, we investigate system calls to tackle mobile malware on Android operating system. To do so, we first employed machine learning to extract system ...
Oct 22, 2024 · In this paper, we investigate system calls to tackle mobile malware on Android operating system. To do so, we first employed machine learning to ...
A machine learning based approach to detect malicious android apps using discriminant system calls. https://doi.org/10.1016/j.future.2018.11.021 ·.
The system uses ML classification algorithms like Support Vector Machine (SVM) to improve the malware application detection in the proposed system.
machine learning based approach to detect malicious android apps using discriminant system calls." Future Generation Computer Systems. 94 (2019): 333-350. 15 ...
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In this paper, we propose a machine learning based approach to detect malicious mobile malware Android applications. Our work is able to capture ...
In this paper, we investigate system calls to tackle mobile malware on Android operating system. To do so, we first employed machine learning to extract system ...
In this paper, we critically review past works that have used machine learning to detect Android malware. The review covers supervised, unsupervised, deep ...
This paper provides a clear and comprehensive survey of the state-of-the-art work that detects malapps by characterizing behaviors of apps with various ...
This paper assesses the effectiveness of the total number of 11 attribute sets, including those never evaluated on Android before, using a consistent data ...