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 …
malware is also emerging in an endless stream. Many researchers have studied the …
Malicious application detection in android—a systematic literature review
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 …
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 …
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 …
high-performance metrics using a wide variety of proposed solutions, enables the logical …
A dynamic DL-driven architecture to combat sophisticated Android malware
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 …
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
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 …
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 …
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 …
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 …
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 …
in recent years. The emergence of 5G in the market and limited protocols post a great …