New journal article accepted!

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Our article on “secure feature partitioning” has been accepted at the EURASIP Journal on Information Security! We discuss how to improve the robustness of machine learning models by training ensembles of classifiers based on disjoint sets of features. This provides state-of-the-art security against attackers based on the L0-distance. More information in our article.