DisCTI: Who Needs to Know Timely? Automated Sector-Aware Cyber Threat Intelligence Dissemination

The paper introduces DisCTI, a system that automatically maps cyber threat intelligence (CTI) events to relevant industry sectors using a multilabel classification approach. By creating a dataset of 872 sector‑labelled CTI events and applying a BERT transformer model, the authors achieve a macro‑averaged F1‑score of 0.89, correctly assigning 94.5% of sector labels. This demonstrates that embedding expert knowledge into machine learning can enable timely, sector‑aware CTI dissemination, improving defensive response.

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