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Android Malware Detection
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Evaluating the Robustness of Adversarial Defenses in Malware Detection Systems
OpCode-Based Malware Classification Using Machine Learning and Deep Learning Techniques
BERTDetect: A Neural Topic Modelling Approach for Android Malware Detection
Trust Under Siege: Label Spoofing Attacks against Machine Learning for Android Malware Detection
LAMD: Context-driven Android Malware Detection and Classification with LLMs
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems
XAI and Android Malware Models
MASKDROID: Robust Android Malware Detection with Masked Graph Representations
Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach
Revisiting Static Feature-Based Android Malware Detection
DetectBERT: Towards Full App-Level Representation Learning to Detect Android Malware
Android Malware Detection Based on RGB Images and Multi-feature Fusion
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations
Improving Android Malware Detection Through Data Augmentation Using Wasserstein Generative Adversarial Networks
Unraveling the Key of Machine Learning Solutions for Android Malware Detection
ActDroid: An active learning framework for Android malware detection
Android Malware Detection with Unbiased Confidence Guarantees
MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks
Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection
Efficient Concept Drift Handling for Batch Android Malware Detection Models
Efficient Query-Based Attack against ML-Based Android Malware Detection under Zero Knowledge Setting
LaFiCMIL: Rethinking Large File Classification from the Perspective of Correlated Multiple Instance Learning
On building machine learning pipelines for Android malware detection: a procedural survey of practices, challenges and opportunities
Continuous Learning for Android Malware Detection
Investigating Feature and Model Importance in Android Malware Detection: An Implemented Survey and Experimental Comparison of ML-Based Methods
Mask Off: Analytic-based Malware Detection By Transfer Learning and Model Personalization
Flexible Android Malware Detection Model based on Generative Adversarial Networks with Code Tensor
Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware Detection
Towards a Fair Comparison and Realistic Evaluation Framework of Android Malware Detectors based on Static Analysis and Machine Learning
A two-steps approach to improve the performance of Android malware detectors
Malceiver: Perceiver with Hierarchical and Multi-modal Features for Android Malware Detection
MaMaDroid2.0 -- The Holes of Control Flow Graphs
Android Malware Detection using Feature Ranking of Permissions
Graph Neural Network-based Android Malware Classification with Jumping Knowledge
"How Does It Detect A Malicious App?" Explaining the Predictions of AI-based Android Malware Detector
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.