Detecting android malware and classifying its families in large-scale datasets

B Sun, T Takahashi, T Ban, D Inoue - ACM Transactions on …, 2021 - dl.acm.org
To relieve the burden of security analysts, Android malware detection and its family
classification need to be automated. There are many previous works focusing on using …

Android malware category and family detection and identification using machine learning

AHE Fiky, AE Shenawy, MA Madkour - arXiv preprint arXiv:2107.01927, 2021 - arxiv.org
Android malware is one of the most dangerous threats on the internet, and it's been on the
rise for several years. Despite significant efforts in detecting and classifying android malware …

Lightweight, effective detection and characterization of mobile malware families

KO Elish, MO Elish, HMJ Almohri - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Android malware is an ongoing threat to billions of smart devices' security, ranging from
mobile phones to car infotainment systems. Despite numerous approaches and previous …

Andmfc: Android malware family classification framework

S Türker, AB Can - 2019 IEEE 30th International Symposium on …, 2019 - ieeexplore.ieee.org
As the popularity of Android mobile operating system grows, the number of malicious
software have increased extensively. Therefore, many research efforts have been done on …

Android malware category and family classification using static analysis

CD Nguyen, NH Khoa, KND Doan… - 2023 International …, 2023 - ieeexplore.ieee.org
In recent years, Android malware has been overgrown, challenging malware analysts.
However, there has been a lot of research in detecting and classifying Android malware …

Hybrid classification and clustering algorithm on recent android malware detection

J Xiao, Q Han, Y Gao - Proceedings of the 2021 5th International …, 2021 - dl.acm.org
With the explosion in the popularity of smartphones over the previous decade, mobile
malware appears to be unavoidable. Because Android is an open platform that is fast …

Evaluating machine learning models for Android malware detection: A comparison study

MS Rana, C Gudla, AH Sung - Proceedings of the 2018 VII International …, 2018 - dl.acm.org
Android is the most popular mobile operating system having billions of active users
worldwide that attracted advertisers, hackers, and cybercriminals to develop malware for …

A comprehensive survey on machine learning techniques for android malware detection

V Kouliaridis, G Kambourakis - Information, 2021 - mdpi.com
Year after year, mobile malware attacks grow in both sophistication and diffusion. As the
open source Android platform continues to dominate the market, malware writers consider it …

An android malware detection leveraging machine learning

AS Shatnawi, A Jaradat, TB Yaseen… - Wireless …, 2022 - Wiley Online Library
Android applications have recently witnessed a pronounced progress, making them among
the fastest growing technological fields to thrive and advance. However, such level of growth …

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 …