SoK: The Impact of Unlabelled Data in Cyberthreat Detection. (arXiv:2205.08944v1 [cs.CR])

Machine learning (ML) has become an important paradigm for cyberthreat
detection (CTD) in the recent years. A substantial research effort has been
invested in the development of specialized algorithms for CTD tasks. From the
operational perspective, however, the progress of ML-based CTD is hindered by
the difficulty in obtaining the large sets of labelled data to train ML
detectors. A potential solution to this problem are semisupervised learning
(SsL) methods, which combine small labelled datasets with large amounts of
unlabelled …

arxiv cyberthreat data detection impact