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Most network security datasets do not have comprehensive label assignmentcriteria, hindering the evaluation of the datasets, the training of models, theresults obtained, the comparison with other methods, and the evaluation inreal-life scenarios. There is no labeling ontology nor tools to help assign thelabels, resulting in most analyzed datasets assigning labels in files ordirectory names. This paper addresses the problem of having a better labelingprocess by (i) reviewing the needs of stakeholders of the datasets, fromcreators to model users, (ii) presenting a new ontology of label assignment,(iii) presenting a new tool for assigning structured labels for Zeek networkflows based on the ontology, and (iv) studying the differences betweengenerating labels and consuming labels in real-life scenarios. We conclude thata process for structured label assignment is paramount for advancing researchin network security and that the new ontology-based label assignation rulesshould be published as an artifact of every dataset.

Towards a better labeling process for network security datasets