关键词: 大语言模型, 威胁情报, 自然语言处理, Transformer, 应用挑战

Abstract: In the expansive realm of computational language processing, a revolutionary entity known as large language models has emerged, garnering attention for its profound ability to comprehend intricate language patterns and generate consistent, contextually relevant responses. Large language models, a type of artificial intelligence, have evolved into powerful tools for various tasks, including natural language processing, machine translation, and questionanswering. In the practical application of threat intelligence, these models exhibit exceptional performance, particularly showcasing significant advantages in critical tasks such as entity recognition, event analysis, and relation extraction. Their contextual understanding capabilities enable them to navigate complex threat scenarios effectively, while hierarchical representation learning allows them to capture diverse structural layers within the text. Furthermore, large language models enhance their adaptability to different domains and specific tasks by leveraging knowledge acquired through transfer learning from general language understanding tasks to threat intelligence tasks. This research trend not only propels technological innovation in the field of threat intelligence but also opens new possibilities for more intelligent and efficient threat analysis and response. However, as research advances, challenges such as data heterogeneity and privacy protection need to be addressed to better facilitate the sustainable development of large language models  in the threat intelligence domain.

Key words: large language models, threat intelligence, natural language processing, Transformer, application challenges