Malware Detection

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Overview

Malware detection studies how to distinguish malicious programs from benign ones across settings such as Windows executables, Android apps, ransomware, and software packages. Common approaches analyze static evidence—such as bytes, API calls, metadata, and control-flow graphs—or dynamic behavior from sandboxes, often using machine learning, deep learning, or combinations of both. Current work also explores temporal evaluation and continual learning to handle changing malware, alongside adversarial testing, explainability, and efficient triage. A central challenge is that strong results on standard benchmarks may not transfer to new malware, future time periods, or manipulated samples, while robust analysis must also control false alarms and computational cost.

Latest papers

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57 papers6 papers in the last four weeks, up 50% on the four weeks before. 0.0% of all new papers.

  1. AdaFedXplain: Adaptive Federated Learning with Explainable AI for Ransomware Detection

    Oct 18, 2026Md. Emran Biswas, Md. Delowar Hossain, Mst. Tanbin Yasmin Tanny +3Malware DetectionFederated Learning

    Department of Electronics and Communication Engineering · Department of Computer Science and Engineering, Hajee Mohammad Danesh Science & Technology University, Bangladesh · Department of Data Science and Engineering, Bangladesh University of Business and Technology, Bangladesh +1

  2. Bytes to Threats: Byte-Sequence Transformer For Malware Detection

    Oct 13, 2026Abdelrahman Yassin Eljamal, Abdeltawab HendawiMalware DetectionTransformer

    Department of Computer Science, University of Rhode Island, Kingston, USA

  3. Hardware-Assisted Multi-Stage Ransomware Detection with Adaptive Machine Learning

    Oct 11, 2026Salma Aboelmagd, Md. Rakibul Ahasan, Zhixin Pan +2Malware Detection

    Florida State University, Tallahassee, FL, USA · Stony Brook University, Stony Brook, NY, USA

  4. Pareto-optimal quantum kernel selection for unsupervised anomaly detection on real malware beaconing data

    Oct 7, 2026Boaz Micah, Nadia Milazzo, Maissa Beji +8Quantum Kernel MethodsUnsupervised Anomaly Detection

    Multiverse Computing, Parque Científico y Tecnológico de Gipuzkoa, Paseo de Miramón 170, Planta 2, 20014 Donostia / San Sebastián, Spain · IQM Quantum Computers, 4 rue Royale, 75008 Paris, France · Multiverse Computing, 7 rue de la Croix Martre, 91120 Palaiseau, Paris, France +3

  5. A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders

    Oct 1, 2026Emmanuela Andam, Yasir Abbas Zaidi, Abdelali Hadir +2Meta-LearningMalware Detection

    Artificial Intelligence Research (AIR) Center, University of North Dakota, Grand Forks, ND, USA · School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA · National School of Commerce and Management, Hassan II University, Casablanca, Morocco

  6. A Structured State Space Sequence Model for Multi-Class Classification of Malware

    Oct 1, 2026Emmanuela Andam, Rana Shaaban, Emanuel Grant +1CybersecurityMalware Classification

    Artificial Intelligence Research (AIR) Center · School of Electrical Engineering and Computer Science, College of Engineering & Mines University of North Dakota, Grand Forks, ND 58201, USA

  7. Temporal Generalization and Explanation Stability of Control Flow Graph Neural Networks for Malware Detection

    Sep 21, 2026Md. Asif Sajeed, Md. Nazrul Islam Mondal, Md Ashraful Hossen AkashGraph Neural NetworksDistribution Shift

    Department of Computer Science and Engineering, Rajshahi University of Engineering & Technology, Rajshahi, 6204, Bangladesh

  8. Delphi Scanner: efficient and interpretable static malware detection via API sequence modeling

    Sep 17, 2026Bijied Brahimi, Vincent Cohadon, Gabriel Glazman +3Malware Detection

    Université Paris Cité, Paris, France · Institut Polytechnique de Paris, Télécom Paris, Palaiseau, France

  9. A TTP by TTP Approach: Precise Malware Detection via Malicious TTP Recognition

    Sep 6, 2026Yashovardhan SharmaMalware Detection

    University of Oxford Oxford, United Kingdom

  10. Cost-Aware Hierarchical Multi-Agent Ransomware Detection and Family Attribution under Analysis Budgets

    Sep 4, 2026Mubashar Iqbal, Asifullah Khan, Hifsa Asif +3Malware DetectionMalware Analysis

    Pattern Recognition Lab, DCIS, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Nilore, Islamabad, Pakistan · Deep Learning Lab, Center for Mathematical Sciences, PIEAS, Nilore, Islamabad, Pakistan · Interdisciplinary Research Center for Smart Mobility and Logistics, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia +2

  11. EGAMA-RC: Risk-Calibrated Evidence-Gated Adaptive Malware Analysis for Robust and Interpretable Memory-Forensic Triage

    Aug 24, 2026Isaac Kofi NtiMalware AnalysisMalware Detection

    School of Information Technology, University of Cincinnati, Ohio, USA.

  12. Enhancing Multiclass Malware Classification in Resource-Constrained Environments

    Aug 23, 2026Abdul Khalek Alve, Alif Rahman, Saadman Zaman +2Malware ClassificationMalware Detection

    Department of Computer Science and Engineering BRAC University, Dhaka, Bangladesh

  13. CAM-Guided Saliency Cutout and Image-Based Malware Classification

    Aug 12, 2026Yasaman Ebrahimi, Martin Jurecek, Mark StampData AugmentationMalware Detection

    Department of Computer Science, San Jose State University · Faculty of Information Technology, Czech Technical University in Prague

  14. On the Performance of Malware Detection Classifiers Using Hardware Performance Counters

    Aug 2, 2026Alireza Abolhasani Zeraatkar, Parnian Shabani Kamran, Inderpreet Kaur +3Malware Detection

    ECE Department University of California Davis, United States

  15. Behavioral Grammar: Detecting Adaptive Malware via Tiny Language Model Priors and Second-Order Temporal Analysis

    Aug 1, 2026Zihan LuoUnsupervised Anomaly DetectionMalware Analysis

  16. Guarding Organizations Against Malware Risk: A Novel Graph-Based Malware Detection Method

    Jul 29, 2026Yinan Gao, Jiarong Xu, Xiaohang Zhao +1Graph Representation LearningMalware Detection

    School of Management, Fudan University · School of Information Management and Engineering, Shanghai University of Finance and Economics · Lerner College of Business and Economics, University of Delaware

  17. EXE-Bench: Ranking the Tradeoffs of AI-based Windows Malware Detectors for Real-World Usability

    Jul 27, 2026Andrea Ponte, Daniel Gibert, Matous Kozak +5Efficient InferenceAdversarial Robustness

    Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, Italy · Artificial Intelligence Research Institute (IIIA-CSIC), Spain · Department of Information Security at Faculty of Information Technology, CTU in Prague, Czech Republic +2

  18. Leveraging Interpretable Tsetlin Machine for PDF Malware Detection

    Jul 10, 2026Rahul JaiswalMalware Detection

    The Centre for Artificial Intelligence Research (CAIR) · Department of ICT, University of Agder, Norway

  19. Detecting Ladder Logic Bombs in IEC 61131-3 PLC Programs using ESBMC-PLC+: A Formal Verification Approach with Trigger Synthesis

    Jul 9, 2026Pierre Dantas, Lucas Cordeiro, Waldir JuniorIndustrial Control System SecurityCybersecurity

    Electrical Engineering Federal University of Amazonas (UFAM) Manaus, AM, Brazil

  20. Agentic SABRE: An Uncertainty-Aware Neuro-Symbolic Multi-Agent Framework for Adaptive Ransomware Detection

    Jul 5, 2026Henry Kabuye, Biju Issac, Jeyamohan NeeraMalware ClassificationNeuro-Symbolic AI

    School of Computer Science, Northumbria University, Newcastle Upon Tyne, UK

  21. ThreatVisionAI: A Hybrid CNN-ViT Framework for Image-Based Malware Classification

    Jul 4, 2026Allyson Taylor, Prashanth BusiReddyGariHybrid CNN-Transformer ArchitecturesMalware Classification

    Department of Mathematics & Computer Science University of North Carolina Pembroke

  22. LLM-Enhanced Hierarchical Heterogeneous Graph Representation Learning for Malicious Python Package Detection

    Jul 3, 2026Hang Gao, Xiaoyu Chen, Baoquan Cui +4Heterogeneous GNNsHierarchical Representation Learning

    Institute of Software, Chinese Academy of Sciences · University of Chinese Academy of Sciences

  23. Hamm-Grams: An Algorithm for Mining Regular Expressions of Bytes

    Jul 1, 2026Derek Everett, Edward Raff, James HoltMalware ClassificationMalware Analysis

    Amazon, Baltimore, USA · CrowdStrike, Austin, USA

  24. A Hybrid Framework For Crypto-Ransomware Detection In Enterprise Shared Storage

    Jun 29, 2026Gervais Hatungimana, Abdun Naser Mahmood, Mohammad Jabed Morshed ChowdhuryNetwork Intrusion DetectionCybersecurity

    Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia

  25. A Multi-task Mixture of Experts Framework for Malware Classification, Packing Detection, and Family Attribution

    Jun 29, 2026Jithin S., Roshin Sleeba C., Anvin Mariya P. B. +4Multi-Task LearningMalware Classification

    Department of Computer Applications, Cochin University of Science and Technology, India · Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy

  26. Multi-View Decompilation for LLM-Based Malware Classification

    Jun 18, 2026Bercan Turkmen, Vyas RainaSoftware Reverse EngineeringLLM Prompting

    Independent Researcher · SPARK

  27. ViPER: Vision-based Packing-Aware Encoder for Robust Malware Detection

    Jun 11, 2026Fatima Qaiser, Bisma Tahir, Muhammad Abid Mughal +1Malware ClassificationMalware Analysis

    Department of Computer & Information Sciences, Pakistan Institute of Engineering & Applied Sciences (PIEAS), Islamabad, Pakistan

  28. MOLOT System Card: Malicious Operational Logic Observation Transformer

    Jun 5, 2026Daniil Lopatkin, Maksim Mitrofanov, Stanislav Rakovsky +1Static Code AnalysisMalware Classification

    Data Science & ML Dept. Positive Technologies False Positive Community

  29. AMD-FCG: An Enhanced Function Call Graph Dataset with Integrated Topological Features for Malware Detection and Classification

    Jun 5, 2026Parthajit Borah, Sakshi Singh, D. K. Bhattacharyya +1Malware ClassificationMalware Analysis

    School of Cyber Security and Digital Forensics, National Forensic Sciences University,Guwahati. · Department of Computer Science and Engineering, Tezpur University, Tezpur, 784028, Assam, India. · Computer Science, College of Engineering and Applied Science, University of Colorado,Colorado Springs, CO 80933-7150, Colorado, USA.

  30. A Hybrid Approach For Malware Classification Using Secondary Features Fusion

    Jun 2, 2026Raja Khurram Shahzad, Muhammad Mustaqeem, Haroon ElahiMalware ClassificationMalware Analysis

    Department of Computer and System Science, Mid Sweden University, Östersund Campus, Jämtland, Sweden. · Department of Engineering, Arbisoft (Pvt.) Ltd., Lahore, Punjab, Pakistan. · Department of Computing Science and Engineering, Chalmers University of Technology, Gothenburg, Västerbotten, Sweden.