Using a Collated Cybersecurity Dataset for Machine Learning and Artificial Intelligence
This work addresses cybersecurity challenges for researchers and practitioners by providing a new dataset, but it is incremental as it applies existing methods to new data.
The paper tackled the problem of cybersecurity modeling by introducing the BRON dataset, amalgamated from public sources, and demonstrated its use in predicting threat techniques and attack patterns, though no concrete numbers were provided.
Artificial Intelligence (AI) and Machine Learning (ML) algorithms can support the span of indicator-level, e.g. anomaly detection, to behavioral level cyber security modeling and inference. This contribution is based on a dataset named BRON which is amalgamated from public threat and vulnerability behavioral sources. We demonstrate how BRON can support prediction of related threat techniques and attack patterns. We also discuss other AI and ML uses of BRON to exploit its behavioral knowledge.