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ACTIC: A Large Language Model‐Based Method for Threat Intelligence Perception

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Published in:IET Communications
Format: Online Article RSS Article
Published: 2026
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container_title IET Communications
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discipline_display Communications
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genre Journal Article
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institution FRELIP
journal_source_facet IET Communications
last_indexed 2026-06-20T21:40:03.057Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle ACTIC: A Large Language Model‐Based Method for Threat Intelligence Perception
Communications
General
Communications
sub_discipline_display General
sub_discipline_facet General
subject_display Communications
General
Communications
subject_facet Communications
General
Communications
title ACTIC: A Large Language Model‐Based Method for Threat Intelligence Perception
title_alt ACTIC: Un método basado en modelos de lenguaje grandes para la percepción de inteligencia de amenazas
ACTIC : une méthode basée sur les grands modèles de langage pour la perception des menaces
ACTIC: Um Método Baseado em Modelo de Linguagem Grande para Percepção de Inteligência de Ameaças
title_auth ACTIC: A Large Language Model‐Based Method for Threat Intelligence Perception
title_es_txt ACTIC: Un método basado en modelos de lenguaje grandes para la percepción de inteligencia de amenazas
title_fr_txt ACTIC : une méthode basée sur les grands modèles de langage pour la perception des menaces
title_full ACTIC: A Large Language Model‐Based Method for Threat Intelligence Perception
title_fullStr ACTIC: A Large Language Model‐Based Method for Threat Intelligence Perception
title_full_unstemmed ACTIC: A Large Language Model‐Based Method for Threat Intelligence Perception
title_pt_txt ACTIC: Um Método Baseado em Modelo de Linguagem Grande para Percepção de Inteligência de Ameaças
title_short ACTIC: A Large Language Model‐Based Method for Threat Intelligence Perception
title_sort actic: a large language model‐based method for threat intelligence perception
topic Communications
General
Communications
url https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cmu2.70162?af=R