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Android Malware Detection

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Showing 1–50 of 76 papers

TitleStatusHype
MADCAT: Combating Malware Detection Under Concept Drift with Test-Time Adaptation—0
Evaluating the Robustness of Adversarial Defenses in Malware Detection SystemsCode0
OpCode-Based Malware Classification Using Machine Learning and Deep Learning Techniques—0
BERTDetect: A Neural Topic Modelling Approach for Android Malware Detection—0
Trust Under Siege: Label Spoofing Attacks against Machine Learning for Android Malware Detection—0
LAMD: Context-driven Android Malware Detection and Classification with LLMs—0
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems—0
Crystal ball: From innovative attacks to attack effectiveness classifierCode0
XAI and Android Malware Models—0
MASKDROID: Robust Android Malware Detection with Masked Graph RepresentationsCode1
Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach—0
Revisiting Static Feature-Based Android Malware Detection—0
DetectBERT: Towards Full App-Level Representation Learning to Detect Android MalwareCode0
Android Malware Detection Based on RGB Images and Multi-feature Fusion—0
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious CorrelationsCode0
Improving Android Malware Detection Through Data Augmentation Using Wasserstein Generative Adversarial Networks—0
Unraveling the Key of Machine Learning Solutions for Android Malware Detection—0
ActDroid: An active learning framework for Android malware detection—0
Android Malware Detection with Unbiased Confidence Guarantees—0
MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion AttacksCode1
Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection—0
Efficient Concept Drift Handling for Batch Android Malware Detection ModelsCode0
Efficient Query-Based Attack against ML-Based Android Malware Detection under Zero Knowledge SettingCode1
LaFiCMIL: Rethinking Large File Classification from the Perspective of Correlated Multiple Instance Learning—0
On building machine learning pipelines for Android malware detection: a procedural survey of practices, challenges and opportunities—0
Continuous Learning for Android Malware DetectionCode1
Investigating Feature and Model Importance in Android Malware Detection: An Implemented Survey and Experimental Comparison of ML-Based Methods—0
Mask Off: Analytic-based Malware Detection By Transfer Learning and Model Personalization—0
Flexible Android Malware Detection Model based on Generative Adversarial Networks with Code Tensor—0
Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware DetectionCode0
Towards a Fair Comparison and Realistic Evaluation Framework of Android Malware Detectors based on Static Analysis and Machine LearningCode0
A two-steps approach to improve the performance of Android malware detectors—0
Malceiver: Perceiver with Hierarchical and Multi-modal Features for Android Malware Detection—0
MaMaDroid2.0 -- The Holes of Control Flow GraphsCode0
Android Malware Detection using Feature Ranking of Permissions—0
Graph Neural Network-based Android Malware Classification with Jumping Knowledge—0
"How Does It Detect A Malicious App?" Explaining the Predictions of AI-based Android Malware Detector—0
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware DetectionCode0
Can We Leverage Predictive Uncertainty to Detect Dataset Shift and Adversarial Examples in Android Malware Detection?Code1
DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection based on Image Representation of BytecodeCode1
heterogeneous temporal graph transformer: an intelligent system for evolving android malware detectionCode1
Data Augmentation for Opcode Sequence Based Malware Detection—0
Deep Learning for Android Malware Defenses: a Systematic Literature ReviewCode1
Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering—0
Identification of Significant Permissions for Efficient Android Malware Detection—0
Collective Intelligence: Decentralized Learning for Android Malware Detection in IoT with Blockchain—0
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning—0
Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware?—0
Why an Android App is Classified as Malware? Towards Malware Classification InterpretationCode1
DL-Droid: Deep learning based android malware detection using real devices—0
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