A systematic overview of the machine learning methods for mobile malware detection

Y Kim, JJ Lee, MH Go, HY Kang… - Security and …, 2022 - Wiley Online Library
With the deployment of the 5G cellular system, the upsurge of diverse mobile applications
and devices has increased the potential challenges and threats posed to users. Industry and …

A novel Android malware detection system: adaption of filter-based feature selection methods

DÖ Şahin, OE Kural, S Akleylek, E Kılıç - Journal of Ambient Intelligence …, 2023 - Springer
Android is the most preferred mobile operating system in the world. Applications are
available from both official application repositories and other application stores. For these …

A comprehensive review on permissions-based Android malware detection

Y Sharma, A Arora - International Journal of Information Security, 2024 - Springer
The first Android-ready “G1” phone debuted in late October 2008. Since then, the growth of
Android malware has been explosive, analogous to the rise in the popularity of Android. The …

[HTML][HTML] GANG-MAM: GAN based engine for modifying android malware

G Renjith, S Laudanna, S Aji, CA Visaggio, P Vinod - SoftwareX, 2022 - Elsevier
Malware detectors based on machine learning are vulnerable to adversarial attacks.
Generative Adversarial Networks (GAN) are architectures based on Neural Networks that …

基于特征选择的恶意Android 应用检测方法.

潘建文, 张志华, 林高毅… - Journal of Computer …, 2023 - search.ebscohost.com
随着移动互联网和Android 操作系统的快速发展, 运行于Android 系统的应用程序同样发展迅速,
但隐藏在其中的恶意应用对用户的财产和隐私安全带来了严重威胁. 针对Android …

A systematic literature review on the mobile malware detection methods

Y Kim, JJ Lee, MH Go, HY Kang, K Lee - International Symposium on …, 2021 - Springer
With the advent of the 5G network, the number of mobile users has drastically increased.
Consequently, the users are much more susceptible to cyber-attacks such as mobile …

MalVulDroid: Tracing Vulnerabilities from Malware in Android using Natural Language Processing

S Garg, N Baliyan - Journal of Web Engineering, 2022 - ieeexplore.ieee.org
The Android operating system is often inflicted with mobile malware attacks, which occur
due to some system loopholes or vulnerabilities. One malware can exploit numerous …

Feature selection based on popularity and value contrast for Android malware classification

P Van Huong, H Van Hiep… - 2022 14th International …, 2022 - ieeexplore.ieee.org
This study proposes a new approach for feature selection in the Android malware detection
problem based on the popularity and contrast in a multi-target approach. The popularity of a …

[PDF][PDF] An efficient Android malware detection method using Borutashap algorithm

S Sharma, RC Prachi, K Khanna - Int. J. Exp. Res. Rev, 2023 - academia.edu
The Android operating system captures the largest global smartphone market share.
However, its popularity and open-source nature have garnered the attention of …

[PDF][PDF] INTEGRATED INFORMATION GAIN WITH EXTRA TREE ALGORITHM FOR FEATURE PERMISSION ANALYSIS IN ANDROID MALWARE CLASSIFICATION

HA AL-KAAF - 2022 - eprints.utm.my
The rapid growth of free applications in the android market has led to the fast spread of
malware apps since users store their sensitive personal information on their mobile devices …