Machine learning algorithm for malware detection: taxonomy, current challenges and future directions
Malware has emerged as a cyber security threat that continuously changes to target
computer systems, smart devices, and extensive networks with the development of …
computer systems, smart devices, and extensive networks with the development of …
NATICUSdroid: A malware detection framework for Android using native and custom permissions
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 …
made it an easy and accessible target for malware. In the past few years, the Android …
A method for automatic android malware detection based on static analysis and deep learning
The computers nowadays are being replaced by the smartphones for the most of the internet
users around the world, and Android is getting the most of the smartphone systems' market …
users around the world, and Android is getting the most of the smartphone systems' market …
An ensemble approach based on fuzzy logic using machine learning classifiers for Android malware detection
İ Atacak - Applied Sciences, 2023 - mdpi.com
In this study, a fuzzy logic-based dynamic ensemble (FL-BDE) model was proposed to
detect malware exposed to the Android operating system. The FL-BDE model contains a …
detect malware exposed to the Android operating system. The FL-BDE model contains a …
Android malware classification using optimized ensemble learning based on genetic algorithms
The continuous increase in Android malware applications (apps) represents a significant
danger to the privacy and security of users' information. Therefore, effective and efficient …
danger to the privacy and security of users' information. Therefore, effective and efficient …
Hybrid classification of Android malware based on fuzzy clustering and the gradient boosting machine
AA Taha, SJ Malebary - Neural Computing and Applications, 2021 - Springer
The widespread use of smartphones in recent years has led to a significant rise in the
sophistication and number of Android malicious applications (apps) targeting smartphone …
sophistication and number of Android malicious applications (apps) targeting smartphone …
Android malware detection using hybrid ANFIS architecture with low computational cost convolutional layers
Background Android is the most widely used operating system all over the world. Due to its
open nature, the Android operating system has become the target of malicious coders …
open nature, the Android operating system has become the target of malicious coders …
A comparison of features for android malware detection
M Leeds, M Keffeler, T Atkison - Proceedings of the SouthEast …, 2017 - dl.acm.org
With the increase in mobile device use, there is a greater need for increasingly sophisticated
malware detection algorithms. The research presented in this paper examines two types of …
malware detection algorithms. The research presented in this paper examines two types of …
Fuzzy integral-based multi-classifiers ensemble for android malware classification
One of the most commonly used operating systems for smartphones is Android. The open-
source nature of the Android operating system and the ability to include third-party Android …
source nature of the Android operating system and the ability to include third-party Android …
A deep camouflage: evaluating android's anti-malware systems robustness against hybridization of obfuscation techniques with injection attacks
The threats facing smartphones have become one of the most dangerous cyberspace
threats; therefore, many solutions have been developed in the commercial or academic …
threats; therefore, many solutions have been developed in the commercial or academic …