Game-Theoretic Explainable AI for Ensemble-Boosting Models in Early Malware Prediction for Computer Systems
Abstract Malware continues to pose a critical threat to computing systems, with modern techniques often bypassing traditional signature-based defenses. Ensemble-boosting classifiers, including GBC, XGBoost, AdaBoost, LightGBM, and CatBoost, have shown strong predictive performance for malware detect...
I tiakina i:
| Ngā kaituhi matua: | , , , |
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| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
Springer
2025-11-01
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| Rangatū: | International Journal of Computational Intelligence Systems |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1007/s44196-025-01011-2 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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