TIJERE uses multisequence labeling representation and SecureBERT+ to reach F1 scores above 0.93 for NER and 0.98 for relation extraction on a new jointly labeled cybersecurity dataset DNRTI-JE.
An end-to-end en tity and relation joint extraction model for cyber threat intellige nce
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TIJERE: A Novel Threat Intelligence Joint Extraction Model Based on Analyst Expert Knowledge
TIJERE uses multisequence labeling representation and SecureBERT+ to reach F1 scores above 0.93 for NER and 0.98 for relation extraction on a new jointly labeled cybersecurity dataset DNRTI-JE.