Malware detection using deep learning and correlation-based feature selection
Malware is one of the most frequent cyberattacks, with its prevalence growing daily across
the network. Malware traffic is always asymmetrical compared to benign traffic, which is …
the network. Malware traffic is always asymmetrical compared to benign traffic, which is …
[HTML][HTML] Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey
Mobile devices have become an essential element in our day-to-day lives. The chances of
mobile attacks are rapidly increasing with the growing use of mobile devices. Exploiting …
mobile attacks are rapidly increasing with the growing use of mobile devices. Exploiting …
[HTML][HTML] Android Malware Detection and Identification Frameworks by Leveraging the Machine and Deep Learning Techniques: A Comprehensive Review
The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …
the threat of malware to computer system, android-based smart phones, Internet of Things …
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 …
Performance Comparison of Supervised Learning Using Non-Neural Network and Neural Network
Currently, the development of mobile phones and mobile applications based on the Android
operating system is increasing rapidly. Many new companies and startups are digitally …
operating system is increasing rapidly. Many new companies and startups are digitally …
Android malware defense through a hybrid multi-modal approach
The rapid proliferation of Android apps has given rise to a dark side, where increasingly
sophisticated malware poses a formidable challenge for detection. To combat this evolving …
sophisticated malware poses a formidable challenge for detection. To combat this evolving …
Machine learning-based adaptive genetic algorithm for android malware detection in auto-driving vehicles
The growing trend toward vehicles being connected to various unidentified devices, such as
other vehicles or infrastructure, increases the possibility of external attacks on “vehicle …
other vehicles or infrastructure, increases the possibility of external attacks on “vehicle …
A new approach to android malware detection using fuzzy logic-based simulated annealing and feature selection
The use of smartphones with the Android operating system has been high in the last
decade, with the transformation of works and services from traditional shape to mechanized …
decade, with the transformation of works and services from traditional shape to mechanized …
Android APK Identification using Non Neural Network and Neural Network Classifier
The purpose of this study is to identify Android APK files by classifying them using Artificial
Neural Network (ANN) and Non Neural Network (NNN). The ANN is Multi-Layer Perceptron …
Neural Network (ANN) and Non Neural Network (NNN). The ANN is Multi-Layer Perceptron …
ChatGPT-driven machine learning code generation for android malware detection
Android is a widely used operating system, primarily found on mobile phones and tablets.
Applications (commonly known as “apps”) for android can be easily installed from Google …
Applications (commonly known as “apps”) for android can be easily installed from Google …