M. Athallah

Federated Learning for Malware Image Classification under Data Heterogeneity

This paper presents an empirical study of federated MIC under varying degrees of data heterogeneity across three popular malware image datasets, and proposes an entropy-aware client selection strategy that filters candidate client sub-sets based on class entropy and shows that this strategy outperforms standard random...