AdaFedXplain: Adaptive Federated Learning with Explainable AI for Ransomware Detection
Attacks using ransomware have developed into complex multiphase campaigns that target vital infrastructure, resulting in annual damages of billions of dollars. Conventional detection techniques are ineffective against zero-day variations, and privacy issues are raised by centralized machine learning algorithms. Federated learning allows for cooperative model training without data sharing, however current FL approaches suffer from explainability issues, high communication cost, and non-IID data heterogeneity. In this study, we present AdaFedXplain, an explainable AI-based adaptive federated learning system for ransomware detection. Our approach includes progressive XGBoost complexity to av...
| Authors | Md. Emran Biswas, Md. Delowar Hossain, Mst. Tanbin Yasmin Tanny et al. |
|---|---|
| Primary category | cs.CR |
| Published | 18 October 2026 |
| Last updated at source | 18 October 2026 |
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