LLM-Based Weak Annotation for Cybersecurity Tweet Classification: A Teacher-Student Framework
Cyber threat intelligence (CTI) relies on the timely identification of emerging threats, enabling organizations and security analysts to support situational awareness and decision-making. Social media platforms such as X (formerly Twitter) have become valuable CTI sources because vulnerabilities and attack activities are often discussed there before appearing in formal reports. However, the rapid growth of cybersecurity discussions on social media has created more content than domain experts can realistically review and annotate, making labeled data a major bottleneck for developing supervised learning approaches. While large language models (LLMs) have shown promise as weak annotators in...
| Authors | Ferry Afit Kurniawan, Kazushi Okamoto, Koki Karube et al. |
|---|---|
| Primary category | cs.CL |
| Published | 15 October 2026 |
| Last updated at source | 15 October 2026 |
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