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Android Malware Detection

Papers

Showing 125 of 76 papers

TitleStatusHype
MADCAT: Combating Malware Detection Under Concept Drift with Test-Time Adaptation0
Evaluating the Robustness of Adversarial Defenses in Malware Detection SystemsCode0
OpCode-Based Malware Classification Using Machine Learning and Deep Learning Techniques0
BERTDetect: A Neural Topic Modelling Approach for Android Malware Detection0
Trust Under Siege: Label Spoofing Attacks against Machine Learning for Android Malware Detection0
LAMD: Context-driven Android Malware Detection and Classification with LLMs0
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems0
Crystal ball: From innovative attacks to attack effectiveness classifierCode0
XAI and Android Malware Models0
MASKDROID: Robust Android Malware Detection with Masked Graph RepresentationsCode1
Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach0
Revisiting Static Feature-Based Android Malware Detection0
Android Malware Detection Based on RGB Images and Multi-feature Fusion0
DetectBERT: Towards Full App-Level Representation Learning to Detect Android MalwareCode0
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 Networks0
Unraveling the Key of Machine Learning Solutions for Android Malware Detection0
ActDroid: An active learning framework for Android malware detection0
Android Malware Detection with Unbiased Confidence Guarantees0
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 Detection0
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 Learning0
On building machine learning pipelines for Android malware detection: a procedural survey of practices, challenges and opportunities0
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