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 developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …

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 …

A review on the use of deep learning in android malware detection

A Naway, Y Li - arXiv preprint arXiv:1812.10360, 2018 - arxiv.org
Android is the predominant mobile operating system for the past few years. The prevalence
of devices that can be powered by Android magnetized not merely application developers …

[HTML][HTML] Android malware detection: mission accomplished? A review of open challenges and future perspectives

A Guerra-Manzanares - Computers & Security, 2023 - Elsevier
The vast body of machine learning based Android malware detection research, reporting
high-performance metrics using a wide variety of proposed solutions, enables the logical …

A dynamic DL-driven architecture to combat sophisticated Android malware

I Bibi, A Akhunzada, J Malik, J Iqbal, A Musaddiq… - IEEE …, 2020 - ieeexplore.ieee.org
The predominant Android operating system has captured enormous attention globally not
only in smart phone industry but also for varied smart devices. The open architecture and …

Dexbert: Effective, task-agnostic and fine-grained representation learning of android bytecode

T Sun, K Allix, K Kim, X Zhou, D Kim… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
The automation of an increasingly large number of software engineering tasks is becoming
possible thanks to Machine Learning (ML). One foundational building block in the …

On the relativity of time: Implications and challenges of data drift on long-term effective android malware detection

A Guerra-Manzanares, H Bahsi - Computers & Security, 2022 - Elsevier
The vast body of research in the Android malware detection domain has demonstrated that
machine learning can provide high performance for mobile malware detection. However, the …

Android malware detection techniques: A literature review

M Dhalaria, E Gandotra - Recent Patents on Engineering, 2021 - ingentaconnect.com
Objective: This paper provides the basics of Android malware, its evolution and tools and
techniques for malware analysis. Its main aim is to present a review of the literature on …

Hybrid machine learning model for malware analysis in android apps

S Bashir, F Maqbool, FH Khan, AS Abid - Pervasive and Mobile Computing, 2024 - Elsevier
Android smartphones have been widely adopted across the globe. They have the capability
to access private and confidential information resulting in these devices being targeted by …

[PDF][PDF] Datdroid: Dynamic analysis technique in android malware detection

R Thangavelooa, WW Jinga, CK Lenga… - … Journal on Advanced …, 2020 - researchgate.net
Android system has become a target for malware developers due to its huge market globally
in recent years. The emergence of 5G in the market and limited protocols post a great …