A comparison of features for android malware detection

M Leeds, M Keffeler, T Atkison - Proceedings of the SouthEast …, 2017 - dl.acm.org
With the increase in mobile device use, there is a greater need for increasingly sophisticated
malware detection algorithms. The research presented in this paper examines two types of …

Preliminary results of applying machine learning algorithms to android malware detection

M Leeds, T Atkison - 2016 International Conference on …, 2016 - ieeexplore.ieee.org
As the use of mobile devices continues to increase, so does the need for sophisticated
malware detection algorithms. The preliminary research presented in this paper focuses on …

[PDF][PDF] Examining features for Android malware detection

M Leeds, M Keffeler, T Atkison - Proceedings of the International …, 2017 - dcsl.cs.ua.edu
With the constantly increasing use of mobile devices, the need for effective malware
detection algorithms is constantly growing. The research presented in this paper expands …

Android application analysis using machine learning techniques

T Takahashi, T Ban - AI in Cybersecurity, 2019 - Springer
The amount of malware that target Android terminals is growing. Malware applications are
distributed to Android terminals in the form of Android Packages (APKs), similar to other …

Analyzing and comparing the effectiveness of various machine learning algorithms for Android malware detection

MS Akhtar - Advances in Mobile Learning Educational Research, 2023 - syncsci.com
Android is the most extensively adopted mobile operating system in the world. The free third-
party programmes that may be downloaded and installed contribute to this success by …

Dynamic permissions based android malware detection using machine learning techniques

A Mahindru, P Singh - Proceedings of the 10th innovations in software …, 2017 - dl.acm.org
Android is by far the most widely used mobile phone operating system around. However,
Android based applications are highly vulnerable to various types of malware attacks …

Android malware detection using category-based machine learning classifiers

H Ali Alatwi, T Oh, E Fokoue, B Stackpole - Proceedings of the 17th …, 2016 - dl.acm.org
Android malware growth has been increasing dramatically as well as the diversity and
complicity of their developing techniques. Machine learning techniques have been applied …

Performance evaluation on permission-based detection for android malware

CY Huang, YT Tsai, CH Hsu - … and Applications-Volume 2: Proceedings of …, 2013 - Springer
It is a straightforward idea to detect a harmful mobile application based on the permissions it
requests. This study attempts to explore the possibility of detecting malicious applications in …

SigPID: significant permission identification for android malware detection

L Sun, Z Li, Q Yan, W Srisa-an… - 2016 11th international …, 2016 - ieeexplore.ieee.org
A recent report indicates that a newly developed malicious app for Android is introduced
every 11 seconds. To combat this alarming rate of malware creation, we need a scalable …

Merging permission and api features for android malware detection

M Qiao, AH Sung, Q Liu - 2016 5th IIAI international congress …, 2016 - ieeexplore.ieee.org
The prosperity of mobile devices have been rapidly and drastically reforming the use pattern
and of user habits with computing devices. Android, the most popular mobile operating …