Cover Image

McNdroid: A Longitudinal Multimodal Benchmark for Robust Drift Detection in Android Malware

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kamol, Md Mahmuduzzaman, Lopez, Jesus, Nowmi, Saeefa Rubaiyet, Rivas, Emilia, Haque, Md Ahsanul, Raff, Edward, Piplai, Aritran, Rahman, Mohammad Saidur
Format:	Preprint
Published:	2026
Subjects:	Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LAMDA: A Longitudinal Android Malware Benchmark for Concept Drift Analysis
by: Haque, Md Ahsanul, et al.
Published: (2025)

CITADEL: A Semi-Supervised Active Learning Framework for Malware Detection Under Continuous Distribution Drift
by: Haque, Md Ahsanul, et al.
Published: (2025)

Towards Quantum Machine Learning for Malicious Code Analysis
by: Lopez, Jesus, et al.
Published: (2025)

SoK: Critical Evaluation of Quantum Machine Learning for Adversarial Robustness
by: Nowmi, Saeefa Rubaiyet, et al.
Published: (2025)

ADAPT: A Pseudo-labeling Approach to Combat Concept Drift in Malware Detection
by: Alam, Md Tanvirul, et al.
Published: (2025)

FreeMOCA: Memory-Free Continual Learning for Malicious Code Analysis
by: Asadi, Zahra, et al.
Published: (2026)

Semantic-Aware Contrastive Fine-Tuning: Boosting Multimodal Malware Classification with Discriminative Embeddings
by: Sanchez, Ivan Montoya, et al.
Published: (2025)

Adapting Under Fire: Multi-Agent Reinforcement Learning for Adversarial Drift in Network Security
by: Rivas, Emilia, et al.
Published: (2025)

MAD-OOD: A Deep Learning Cluster-Driven Framework for an Out-of-Distribution Malware Detection and Classification
by: Ige, Tosin, et al.
Published: (2025)

Integrating APK Image and Text Data for Enhanced Threat Detection: A Multimodal Deep Learning Approach to Android Malware
by: Arifin, Md Mashrur, et al.
Published: (2026)

An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey
by: Ige, Tosin, et al.
Published: (2024)

Deep Learning-Based Speech and Vision Synthesis to Improve Phishing Attack Detection through a Multi-layer Adaptive Framework
by: Ige, Tosin, et al.
Published: (2024)

Impugan: Learning Conditional Generative Models for Robust Data Imputation
by: Mahmud, Zalish, et al.
Published: (2025)

Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
by: Kuikel, Shova, et al.
Published: (2025)

FALCON: Autonomous Cyber Threat Intelligence Mining with LLMs for IDS Rule Generation
by: Mitra, Shaswata, et al.
Published: (2025)

Overlapping Community Detection using Dynamic Dilated Aggregation in Deep Residual GCN
by: Muttakin, Md Nurul, et al.
Published: (2022)

Diagnosing and Mitigating Domain Shift in Permission-Based Android Malware Detection
by: Islam, Md Rafid
Published: (2026)

Empathy by Design: Aligning Large Language Models for Healthcare Dialogue
by: Umucu, Emre, et al.
Published: (2025)

Combined Toxicity of Polyamide Microplastics and Fenitrothion Impairs Growth, Intestinal Integrity, and GH – IGF Axis in Nile Tilapia
by: Mobassir Bin Anwar, et al.
Published: (2026)

Adversarial Vulnerability Under Temporal Concept Drift: A Longitudinal Study of Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2026)

Minerva: Reinforcement Learning with Verifiable Rewards for Cyber Threat Intelligence LLMs
by: Alam, Md Tanvirul, et al.
Published: (2026)

Probabilistic Feature Imputation and Uncertainty-Aware Multimodal Federated Aggregation
by: Shahid, Nafis Fuad, et al.
Published: (2026)

First‐Principles DFT Investigation of Physical and Superconducting Properties in Cesium‐Based Ternary Compounds CsT 2 Si 2 (T = Ni, In, Ga, Rh, Ta, and Ir)
by: Rifat Sarker Apu, et al.
Published: (2026)

Understanding Concept Drift with Deprecated Permissions in Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025)

MADAR: Efficient Continual Learning for Malware Analysis with Distribution-Aware Replay
by: Rahman, Mohammad Saidur, et al.
Published: (2025)

AgentCyTE: Leveraging Agentic AI to Generate Cybersecurity Training & Experimentation Scenarios
by: Rodriguez, Ana M., et al.
Published: (2025)

Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2025)

Combating Concept Drift with Explanatory Detection and Adaptation for Android Malware Classification
by: He, Yiling, et al.
Published: (2024)

On Benchmarking Code LLMs for Android Malware Analysis
by: He, Yiling, et al.
Published: (2025)

R+R: Revisiting Static Feature-Based Android Malware Detection using Machine Learning
by: Alam, Md Tanvirul, et al.
Published: (2024)

Physics-Based Benchmarking Metrics for Multimodal Synthetic Images
by: Gupta, Kishor Datta, et al.
Published: (2025)

Evaluating Generalization Mechanisms in Autonomous Cyber Attack Agents
by: Lukáš, Ondřej, et al.
Published: (2026)

MORPH: Towards Automated Concept Drift Adaptation for Malware Detection
by: Alam, Md Tanvirul, et al.
Published: (2024)

Use of Graph Neural Networks in Aiding Defensive Cyber Operations
by: Mitra, Shaswata, et al.
Published: (2024)

Enhancing classroom teaching with LLMs and RAG
by: Mullins, Elizabeth A, et al.
Published: (2024)

GHTM: A Graph-based Hybrid Topic Modeling Approach with a Benchmark Dataset for the Low-Resource Bengali Language
by: Haque, Farhana, et al.
Published: (2025)

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset
by: Abedin, Md Min-Ha-Zul, et al.
Published: (2026)

Concept Drift Adaptation Using Self-Supervised and Reinforcement Learning In Android Malware Detection
by: Sabbah, Ahmed, et al.
Published: (2026)

EMBER2024 -- A Benchmark Dataset for Holistic Evaluation of Malware Classifiers
by: Joyce, Robert J., et al.
Published: (2025)

Security Vulnerabilities in Software Supply Chain for Autonomous Vehicles
by: Haque, Md Wasiul, et al.
Published: (2025)