Designing Robust Deep Learning Classifiers for Image-based Malware Analysis
Contributo in Atti di convegno
Data di Pubblicazione:
2022
Abstract:
Deep Learning models demonstrated high accuracies performance in malware classification, but they are still lacking "explainability"to ensure robustness and reliability in the generated prediction. In this short contribution, we summarize the researches that we conducted in the latest years in the Malware Analysis field.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
component; formatting; insert; style; styling
Elenco autori:
Martinelli, Fabio
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