[HTML][HTML] An in-depth review of machine learning based Android malware detection

A Muzaffar, HR Hassen, MA Lones, H Zantout - Computers & Security, 2022 - Elsevier
It is estimated that around 70% of mobile phone users have an Android device. Due to this
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …

A survey of malware detection in Android apps: Recommendations and perspectives for future research

A Razgallah, R Khoury, S Hallé… - Computer Science …, 2021 - Elsevier
Android has dominated the smartphone market and has become the most popular operating
system for mobile devices. However, security threats in Android applications have also …

Malware analysis in IoT & android systems with defensive mechanism

CS Yadav, J Singh, A Yadav, HS Pattanayak, R Kumar… - Electronics, 2022 - mdpi.com
The Internet of Things (IoT) and the Android operating system have made cutting-edge
technology accessible to the general public. These are affordable, easy-to-use, and open …

Intelligent mobile malware detection using permission requests and API calls

M Alazab, M Alazab, A Shalaginov, A Mesleh… - Future Generation …, 2020 - Elsevier
Malware is a serious threat that has been used to target mobile devices since its inception.
Two types of mobile malware attacks are standalone: fraudulent mobile apps and injected …

Robust deep learning early alarm prediction model based on the behavioural smell for android malware

E Amer, S El-Sappagh - Computers & Security, 2022 - Elsevier
Due to the widespread expansion of the Android malware industry, malicious Android
processes mining became a necessity to understand their behavior. Nevertheless, due to …

Malicious application detection in android—a systematic literature review

T Sharma, D Rattan - Computer Science Review, 2021 - Elsevier
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …

Constructing features for detecting android malicious applications: issues, taxonomy and directions

W Wang, M Zhao, Z Gao, G Xu, H Xian, Y Li… - IEEE …, 2019 - ieeexplore.ieee.org
The number of applications (apps) available for smart devices or Android based IoT (Internet
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …

[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 …

Malware detection: a framework for reverse engineered android applications through machine learning algorithms

B Urooj, MA Shah, C Maple, MK Abbasi… - IEEE Access, 2022 - ieeexplore.ieee.org
Today, Android is one of the most used operating systems in smartphone technology. This is
the main reason, Android has become the favorite target for hackers and attackers …

An Android malware detection system based on machine learning

L Wen, H Yu - AIP conference proceedings, 2017 - pubs.aip.org
The Android smartphone, with its open source character and excellent performance, has
attracted many users. However, the convenience of the Android platform also has motivated …