[HTML][HTML] Machine learning for android malware detection: mission accomplished? a comprehensive review of open challenges and future perspectives
A Guerra-Manzanares - Computers & Security, 2024 - Elsevier
The extensive research in machine learning based Android malware detection showcases
high-performance metrics through a wide range of proposed solutions. Consequently, this …
high-performance metrics through a wide range of proposed solutions. Consequently, this …
[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 …
Quantum Mayfly optimization with encoder-decoder driven LSTM networks for malware detection and classification model
Malware refers to malicious software developed to penetrate or damage a computer system
without any owner's informed consent. It uses target system susceptibilities, like bugs in …
without any owner's informed consent. It uses target system susceptibilities, like bugs in …
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 …
Numerical feature selection and hyperbolic tangent feature scaling in machine learning-based detection of anomalies in the computer network behavior
Anomaly-based intrusion detection systems identify the computer network behavior which
deviates from the statistical model of typical network behavior. Binary classifiers based on …
deviates from the statistical model of typical network behavior. Binary classifiers based on …
AndroMalPack: enhancing the ML-based malware classification by detection and removal of repacked apps for Android systems
Due to the widespread usage of Android smartphones in the present era, Android malware
has become a grave security concern. The research community relies on publicly available …
has become a grave security concern. The research community relies on publicly available …
[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 improved binary owl feature selection in the context of Android malware detection
Recently, the proliferation of smartphones, tablets, and smartwatches has raised security
concerns from researchers. Android-based mobile devices are considered a dominant …
concerns from researchers. Android-based mobile devices are considered a dominant …
Nt-gnn: Network traffic graph for 5g mobile iot android malware detection
T Liu, Z Li, H Long, A Bilal - Electronics, 2023 - mdpi.com
IoT Android application is the most common implementation system in the mobile
ecosystem. As assaults have increased over time, malware attacks will likely happen on 5G …
ecosystem. As assaults have increased over time, malware attacks will likely happen on 5G …
Android APK Identification using Non Neural Network and Neural Network Classifier
D Hindarto, H Santoso - Journal of Computer Science and …, 2021 - jcosine.if.unram.ac.id
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 …