AdaFedXplain: Adaptive Federated Learning with Explainable AI for Ransomware Detection
In this study, we present AdaFedXplain, an explainable AI-based adaptive federated learning system for ransomware detection.
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Key points
- Attacks using ransomware have developed into complex multiphase campaigns that target vital infrastructure, resulting in annual damages of billions of dollars.
- 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.
- Using 62,485 real-world ransomware samples from four OS-based non-IID clients, we compare AdaFedXplain against FedAvg, FedProx, and SCAFFOLD.
- Our system provides a collaborative ransomware detection solution that is efficient and interpretable, while reducing privacy risks through federated learnings data-local training paradigm.
Sources (1)
- [1]AdaFedXplain: Adaptive Federated Learning with Explainable AI for Ransomware DetectionarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 18, 02:55 PM
In this study, we present AdaFedXplain, an explainable AI-based adaptive federated learning system for ransomware detection.
Attacks using ransomware have developed into complex multiphase campaigns that target vital infrastructure, resulting in annual damages of billions of dollars.
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