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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 12, 2021.
Abstract: The immense popularity of smartphones has led to the constant use of these devices for productive and entertainment purposes in daily life. Among the different operating systems, the Android system plays a very important role in the development of mobile technology as it is the most popular operating system. This makes it a target for cyberattack, with severe negative effects in terms of monetary and privacy costs. Thus, this study implements a detection scheme using effective deep learning algorithms (LSTM and MLP). Also, it tests their ability to detect malware by employing private and public datasets, with accuracy of over than 99%.
Abdulaziz Alzubaidi, “Sustainable Android Malware Detection Scheme using Deep Learning Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 12(12), 2021. http://dx.doi.org/10.14569/IJACSA.2021.01212104
@article{Alzubaidi2021,
title = {Sustainable Android Malware Detection Scheme using Deep Learning Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.01212104},
url = {http://dx.doi.org/10.14569/IJACSA.2021.01212104},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {12},
author = {Abdulaziz Alzubaidi}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.