Droidapiminer: Mining api-level features for robust malware detection in android

Y Aafer, W Du, H Yin - Security and Privacy in Communication Networks …, 2013 - Springer
The increasing popularity of Android apps makes them the target of malware authors. To
defend against this severe increase of Android malwares and help users make a better …

NATICUSdroid: A malware detection framework for Android using native and custom permissions

A Mathur, LM Podila, K Kulkarni, Q Niyaz… - Journal of Information …, 2021 - Elsevier
The rapid growth of Android apps and its worldwide popularity in the smartphone market has
made it an easy and accessible target for malware. In the past few years, the Android …

A survey of android malware static detection technology based on machine learning

Q Wu, X Zhu, B Liu - Mobile Information Systems, 2021 - Wiley Online Library
With the rapid growth of Android devices and applications, the Android environment faces
more security threats. Malicious applications stealing usersʼ privacy information, sending …

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 …

[HTML][HTML] On machine learning effectiveness for malware detection in Android OS using static analysis data

V Syrris, D Geneiatakis - Journal of Information Security and Applications, 2021 - Elsevier
Although various security mechanisms have been introduced in Android operating system in
order to enhance its robustness, sheer protection remains an open issue: malicious …

Evaluation of android malware detection based on system calls

M Dimjašević, S Atzeni, I Ugrina… - Proceedings of the 2016 …, 2016 - dl.acm.org
With Android being the most widespread mobile platform, protecting it against malicious
applications is essential. Android users typically install applications from large remote …

Experimental study with real-world data for android app security analysis using machine learning

S Roy, J DeLoach, Y Li, N Herndon… - Proceedings of the 31st …, 2015 - dl.acm.org
Although Machine Learning (ML) based approaches have shown promise for Android
malware detection, a set of critical challenges remain unaddressed. Some of those …

AdDroid: rule-based machine learning framework for android malware analysis

A Mehtab, WB Shahid, T Yaqoob, MF Amjad… - Mobile Networks and …, 2020 - Springer
Recent years have witnessed huge growth in Android malware development. Colossal
reliance on Android applications for day to day working and their massive development …

Significant permission identification for machine-learning-based android malware detection

J Li, L Sun, Q Yan, Z Li, W Srisa-An… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
The alarming growth rate of malicious apps has become a serious issue that sets back the
prosperous mobile ecosystem. A recent report indicates that a new malicious app for …

Madam: Effective and efficient behavior-based android malware detection and prevention

A Saracino, D Sgandurra, G Dini… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Android users are constantly threatened by an increasing number of malicious applications
(apps), generically called malware. Malware constitutes a serious threat to user privacy …