A zero-shot self-improving NER method for cyber threat intelligence via knowledge injection

Abstract The rapid evolution of cyber threats demands efficient entity extraction from Cyber Threat Intelligence (CTI) reports to support proactive analysis and sharing. Current methods for CTI extraction falter due to a lack of domain knowledge, which can lead to the overlooking of critical entitie...

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Autori principali:	Yingchang Jiang, Hao Hu, Yunpeng Li, Feiyang Li, Changzhi Zhao, Canhua Chen, Yuling Liu
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	SpringerOpen 2025-12-01
Serie:	Cybersecurity
Soggetti:	Zero-shot Self-Improving Large language model(LLM) Name entity recognition(NER) Cyber threat intelligence(CTI)
Accesso online:	https://doi.org/10.1186/s42400-025-00503-0
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