Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for Specialized Cyber Threat Intelligence. (arXiv:2207.11076v1 [cs.CR])

Gathering cyber threat intelligence from open sources is becoming
increasingly important for maintaining and achieving a high level of security
as systems become larger and more complex. However, these open sources are
often subject to information overload. It is therefore useful to apply machine
learning models that condense the amount of information to what is necessary.
Yet, previous studies and applications have shown that existing classifiers are
not able to extract specific information about emerging cybersecurity events
due to their …

arxiv augmentation cyber cyber threat data few-shot learning fine-tuning intelligence learning threat intelligence