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.
Information and Communications Security: 23rd Inte rnational Con- ference, ICICS 2021, pp
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CTiKG pipeline improves named entity recognition by 3-4% and relation extraction by up to 8% on DNRTI-AUG-STIX2 and other CTI benchmarks by adding context-aware hybrid NLP and ontology knowledge.
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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.
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Context-aware Entity-Relation Extraction for Threat Intelligence Knowledge Graphs
CTiKG pipeline improves named entity recognition by 3-4% and relation extraction by up to 8% on DNRTI-AUG-STIX2 and other CTI benchmarks by adding context-aware hybrid NLP and ontology knowledge.