A review of android malware detection approaches based on machine learning

K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are develo** rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …

Android source code vulnerability detection: a systematic literature review

J Senanayake, H Kalutarage, MO Al-Kadri… - ACM Computing …, 2023 - dl.acm.org
The use of mobile devices is rising daily in this technological era. A continuous and
increasing number of mobile applications are constantly offered on mobile marketplaces to …

Android mobile malware detection using machine learning: A systematic review

J Senanayake, H Kalutarage, MO Al-Kadri - Electronics, 2021 - mdpi.com
With the increasing use of mobile devices, malware attacks are rising, especially on Android
phones, which account for 72.2% of the total market share. Hackers try to attack …

[PDF][PDF] Efficiency of malware detection in android system: A survey

MA Omer, SR Zeebaree, MA Sadeeq… - Asian Journal of …, 2021 - academia.edu
Smart phones are becoming essential in our lives, and Android is one of the most popular
operating systems. Android OS is wide-ranging in the mobile industry today because of its …

[HTML][HTML] A Bayesian probability model for Android malware detection

SRT Mat, MF Ab Razak, MNM Kahar, JM Arif, A Firdaus - ICT Express, 2022 - Elsevier
The unprecedented growth of mobile technology has generated an increase in malware and
raised concerns over malware threats. Different approaches have been adopted to …

Towards a systematic description of the field using bibliometric analysis: malware evolution

SRT Mat, MF Ab Razak, MNM Kahar, JM Arif… - Scientometrics, 2021 - Springer
Malware is a blanket term for Trojan, viruses, spyware, worms, and other files that are
purposely created to harm computers, mobile devices, or computer networks. Malware …

[PDF][PDF] A comparative study on machine learning and deep learning methods for malware detection

E Ravi, MU Kumar - Journal of Theoretical and Applied Information …, 2022 - jatit.org
ABSTRACT The advent of Artificial Intelligence (AI) and data science with Machine Learning
(ML) and deep learning techniques has paved way for solving many real world problems …

A method for class-imbalance learning in android malware detection

J Guan, X Jiang, B Mao - Electronics, 2021 - mdpi.com
More and more Android application developers are adopting many different methods
against reverse engineering, such as adding a shell, resulting in certain features that cannot …

Android Permission Classifier: a deep learning algorithmic framework based on protection and threat levels

M Ashawa, S Morris - Security and Privacy, 2021 - Wiley Online Library
Recent works demonstrated that Android is the fastest growing mobile OS with the highest
number of users worldwide. Android's popularity is facilitated by factors such as ease of use …

An Analysis of Machine Learning-Based Android Malware Detection Approaches

R Srinivasan, S Karpagam, M Kavitha… - Journal of Physics …, 2022 - iopscience.iop.org
Despite the fact that Android apps are rapidly expanding throughout the mobile ecosystem,
Android malware continues to emerge. Malware operations are on the rise, particularly on …