Authors :
Umar badamasi ibrahim; SaurabhSrivastwa; Manish Verma
Volume/Issue :
Volume 7 - 2022, Issue 4 - April
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3L1Q3wz
DOI :
https://doi.org/10.5281/zenodo.6535823
Abstract :
Android is an open-source Operating System
(OS) that is free and allows for a comprehensive
understanding of its architecture. As a result, lots of
manufacturers, including Samsung, Google Pixel, Sony,
and Motorola, are using this system to create mobile
devices (Mobile phones, smartwatches, and smart
glasses). The use of an operating system leads to an
expeditious growth in the number of Android users. On
the other hand, unethical authors tend to create privacy
devices for the sake of wealth or fame. Even though
practitioners perform encroachment perception studies
such as static analysis, this research examines some
recently published articles from the year 2018 to early
2022. Based on the survey clearly stating that the
android privacy leak uses the android characteristic,
AmpDroid and FlowDroid also play a good role in
detecting malware, later on, machine learning(ML) and
deep learning algorithm is introduced to the system to
find high accuracy and also listed the component and the
stages of the analysis way to detect Android malware
based on its high algorithm effect and accurate result.
Keywords :
Android privacy detection, Static analysis, Machine learning, deep learning algorithms, stages, compone.
Android is an open-source Operating System
(OS) that is free and allows for a comprehensive
understanding of its architecture. As a result, lots of
manufacturers, including Samsung, Google Pixel, Sony,
and Motorola, are using this system to create mobile
devices (Mobile phones, smartwatches, and smart
glasses). The use of an operating system leads to an
expeditious growth in the number of Android users. On
the other hand, unethical authors tend to create privacy
devices for the sake of wealth or fame. Even though
practitioners perform encroachment perception studies
such as static analysis, this research examines some
recently published articles from the year 2018 to early
2022. Based on the survey clearly stating that the
android privacy leak uses the android characteristic,
AmpDroid and FlowDroid also play a good role in
detecting malware, later on, machine learning(ML) and
deep learning algorithm is introduced to the system to
find high accuracy and also listed the component and the
stages of the analysis way to detect Android malware
based on its high algorithm effect and accurate result.
Keywords :
Android privacy detection, Static analysis, Machine learning, deep learning algorithms, stages, compone.
