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A Context-Aware Android Malware Detection Approach Using Machine Learning
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-29407-6_4openalex-snapshot
Static, Dynamic and Intrinsic Features Based Android Malware Detection Using Machine Learning
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Android Malware Detection Using API Calls: A Comparison of Feature Selection and Machine Learning Models
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Android Malware Detection Using Machine Learning Technique
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Mining API Calls and Permissions for Android Malware Detection
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Android Malware Clustering Through Malicious Payload Mining
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Android Malware Detection Based on Network Traffic Using Decision Tree Algorithm
inferredcites →https://doi.org/10.1007/978-981-15-1706-8openalex-snapshot
Machine Learning Approaches in Cyber Security Analytics
inferredcites →https://doi.org/10.1007/978-981-15-5616-6_22openalex-snapshot
Machine Learning Classifiers for Android Malware Detection
inferredcites →https://doi.org/10.1007/978-981-16-3071-2_28openalex-snapshot
“Emerging Trends in Computational Intelligence to Solve Real-World Problems” Android Malware Detection Using Machine Learning
inferredcites →https://doi.org/10.1007/s10664-017-9539-8openalex-snapshot
A multi-view context-aware approach to Android malware detection and malicious code localization
inferredcites →https://doi.org/10.1007/s42452-020-3132-2openalex-snapshot
Android malware detection based on image-based features and machine learning techniques
inferredcites →https://doi.org/10.1016/j.comnet.2020.107138openalex-snapshot
IMCFN: Image-based malware classification using fine-tuned convolutional neural network architecture
inferredcites →https://doi.org/10.1016/j.diin.2018.01.007openalex-snapshot
MalDozer: Automatic framework for android malware detection using deep learning
inferredcites →https://doi.org/10.1016/j.microrel.2019.01.007openalex-snapshot
An Android mutation malware detection based on deep learning using visualization of importance from codes
inferredcites →https://doi.org/10.1016/j.procs.2016.03.028openalex-snapshot
Analysis of Malicious Behavior of Android Apps
inferredcites →https://doi.org/10.1089/big.2018.0175openalex-snapshot
Effects of Distance Measure Choice on K-Nearest Neighbor Classifier Performance: A Review
inferredcites →https://doi.org/10.1109/access.2020.2965646openalex-snapshot
Android Malware Familial Classification Based on DEX File Section Features
inferredcites →https://doi.org/10.1109/bigcomp48618.2020.00-96openalex-snapshot
Enhanced Android Malware Detection: An SVM-Based Machine Learning Approach
inferredcites →https://doi.org/10.1109/ccwc54503.2022.9720753openalex-snapshot
A Survey on Mobile Malware Detection Methods using Machine Learning
inferredcites →https://doi.org/10.1109/cybersa49311.2020.9139664openalex-snapshot
Mobile Botnet Detection: A Deep Learning Approach Using Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/cybersecpods.2017.8074847openalex-snapshot
Malware detection in android based on dynamic analysis
inferredcites →https://doi.org/10.1109/dasc-picom-cbdcom-cyberscitech49142.2020.00094openalex-snapshot
Dynamic Android Malware Category Classification using Semi-Supervised Deep Learning
inferredcites →https://doi.org/10.1109/iccmc53470.2022.9753746openalex-snapshot
A Literature Review on Android Mobile Malware Detection using Machine Learning Techniques
inferredcites →https://doi.org/10.1109/iccsee.2012.97openalex-snapshot
A Feature Selection Method Based on Information Gain and Genetic Algorithm
inferredcites →https://doi.org/10.1109/icimcis51567.2020.9354315openalex-snapshot
Hybrid-Based Malware Analysis for Effective and Efficiency Android Malware Detection
inferredcites →https://doi.org/10.1109/malware.2012.6461012openalex-snapshot
Smartphone malware detection: From a survey towards taxonomy
inferredcites →https://doi.org/10.1109/rivf48685.2020.9140771openalex-snapshot
A Machine Learning Approach for Real Time Android Malware Detection
inferredcites →https://doi.org/10.1109/tetci.2017.2699220openalex-snapshot
Context-Aware, Adaptive, and Scalable Android Malware Detection Through Online Learning
inferredcites →https://doi.org/10.1109/tmc.2022.3197638openalex-snapshot
FlowCog: Context-Aware Semantic Extraction and Analysis of Information Flow Leaks in Android Apps
inferredcites →https://doi.org/10.1145/3139367.3139400openalex-snapshot
Machine Learning and Images for Malware Detection and Classification
inferredcites →https://doi.org/10.1371/journal.pone.0257968openalex-snapshot
A static analysis approach for Android permission-based malware detection systems
inferredcites →https://doi.org/10.14569/ijacsa.2020.0110429openalex-snapshot
Empirical Study on Intelligent Android Malware Detection based on Supervised Machine Learning
inferredcites →https://doi.org/10.14722/ndss.2014.23247openalex-snapshot
Drebin: Effective and Explainable Detection of Android Malware in Your Pocket
inferredcites →https://doi.org/10.26735/krvi8434openalex-snapshot
Analysis of Mobile Malware: A Systematic Review of Evolution and Infection Strategies
inferredcites →https://doi.org/10.30534/ijatcse/2020/4691.52020openalex-snapshot
Android Malware Detection System using Machine Learning
inferredcites →https://doi.org/10.3390/info12050185openalex-snapshot
A Comprehensive Survey on Machine Learning Techniques for Android Malware Detection
inferredcites →https://doi.org/10.5220/0006256706530662openalex-snapshot
Static and Dynamic Analysis of Android Malware
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-47715-7_35openalex-snapshot
Android Malware Detection Using Machine Learning: A Review
inferred← citeshttps://doi.org/10.1007/978-3-031-59100-6_18openalex-snapshot
A Novel Mechanism for Tuning Neural Network for Malware Detection in Android Device
inferred← citeshttps://doi.org/10.1007/978-3-032-28460-0_17openalex-snapshot
A Framework for Improving Anomaly-Based Network Intrusion Detection in IoT Systems Using Hybrid GWO with Jaya
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Toward Intelligent Tracking Down of Malicious Applications Pre-installed on Smartphones Sold in African Emerging Markets
inferred← citeshttps://doi.org/10.1007/s10207-024-00822-2openalex-snapshot
A comprehensive review on permissions-based Android malware detection
inferred← citeshttps://doi.org/10.1007/s10586-024-04484-6openalex-snapshot
Android malware detection using time-aware machine learning approach
inferred← citeshttps://doi.org/10.1016/j.array.2026.101101openalex-snapshot
Memory-resident malware detection using explainable AI and adaptive compression
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PHIGrader: Evaluating the effectiveness of Manifest file components in Android malware detection using Multi Criteria Decision Making techniques
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Mitigating concept drift in malware classification: A temporal and resource-aware evaluation
inferred← citeshttps://doi.org/10.1109/access.2024.3357944openalex-snapshot
Intelligent Pattern Recognition Using Equilibrium Optimizer With Deep Learning Model for Android Malware Detection
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AdaptivePixGuard: Attention-Enhanced Temporal Convolutions for Robust Mobile Pixnapping Detection
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Hybrid Machine Learning Model for Anticipating Cyber Crime Malware in Android: Work on Progress
inferred← citeshttps://doi.org/10.1109/ic2e365635.2025.11167677openalex-snapshot
A High-Performance Malware Detection Using Extra Tree Classifier and Logistic Regression on TUNADROMD Dataset
inferred← citeshttps://doi.org/10.1109/icaaic60222.2024.10575129openalex-snapshot
Intelligent Behavioral Monitoring and Detection of Preinstalled Malicious Applications on Smartphones Sold in Emerging African Markets
inferred← citeshttps://doi.org/10.1109/icci61671.2024.10485163openalex-snapshot
Machine Learning Based Approaches For Android Malware Detection using Hybrid Feature Analysis
inferred← citeshttps://doi.org/10.1109/icdsaai65575.2025.11011597openalex-snapshot
Malware Detection through Memory Dump Analysis by Enhanced Machine Learning Techniques
inferred← citeshttps://doi.org/10.1109/iconat66879.2025.11362663openalex-snapshot
Enhanced Context-Aware Testing for Mobile Applications Using a Hybrid Grammatical Evolution Method
inferred← citeshttps://doi.org/10.1109/icscss64956.2025.11500744openalex-snapshot
Entropy-Driven Multi-Scale Convolutional Neural Networks for Image-based Malware Classification
inferred← citeshttps://doi.org/10.1109/icssas66150.2025.11080800openalex-snapshot
Dynamic Class-Balanced CNN with Hierarchical Feature Extraction for Real-Time Malware Image Classification
inferred← citeshttps://doi.org/10.1109/incit60207.2023.10413140openalex-snapshot
Effects of Malware Detection Parameters on Classical vs Deep ML Techniques
inferred← citeshttps://doi.org/10.22214/ijraset.2024.61156openalex-snapshot
Design and Development of Android App Malware Detector API Using Androguard and Catboost
inferred← citeshttps://doi.org/10.3390/computers14110467openalex-snapshot
Efficient Image-Based Memory Forensics for Fileless Malware Detection Using Texture Descriptors and LIME-Guided Deep Learning
inferred← citeshttps://doi.org/10.3390/e27121252openalex-snapshot
MaSS-Droid: Android Malware Detection Framework Using Multi-Layer Feature Screening and Stacking Integration
inferred← citeshttps://doi.org/10.3390/info14020102openalex-snapshot
Spyware Identification for Android Systems Using Fine Trees
inferred← citeshttps://doi.org/10.3390/info14030193openalex-snapshot
The Effect of the Ransomware Dataset Age on the Detection Accuracy of Machine Learning Models
inferred← citeshttps://doi.org/10.3390/info15060313openalex-snapshot
Correction: AlJarrah et al. A Context-Aware Android Malware Detection Approach Using Machine Learning. Information 2022, 13, 563
inferred← citeshttps://doi.org/10.3390/s25030670openalex-snapshot
MINDPRES: A Hybrid Prototype System for Comprehensive Data Protection in the User Layer of the Mobile Cloud
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