Labeling Hacker Exploits for Proactive Cyber Threat Intelligence: A Deep Transfer Learning Approach

Benjamin M. Ampel; Sagar Samtani; Hongyi Zhu; Steven Ullman; Hsinchun Chen

doi:10.1109/ISI49825.2020.9280548

Labeling Hacker Exploits for Proactive Cyber Threat Intelligence: A Deep Transfer Learning Approach

Benjamin M. Ampel, Sagar Samtani, Hongyi Zhu, Steven Ullman, Hsinchun Chen

Last updated on Jun 9, 2026

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In Plain Terms

This study builds a system that automatically collects and categorizes exploit code shared on hacker forums, turning messy, unlabeled posts into useful early-warning cyber threat intelligence. It uses transfer learning to apply knowledge from professionally labeled exploits to noisy forum data, sorting exploits into eight categories. The proposed model outperforms existing approaches in the literature.

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Benjamin M. Ampel, Sagar Samtani, Hongyi Zhu, Steven Ullman, & Hsinchun Chen (2020). Labeling Hacker Exploits for Proactive Cyber Threat Intelligence: A Deep Transfer Learning Approach. IEEE ISI https://doi.org/10.1109/ISI49825.2020.9280548

Hacker Forums Cyber Threat Intelligence Deep Learning Exploit Labeling

Labeling Hacker Exploits for Proactive Cyber Threat Intelligence: A Deep Transfer Learning Approach

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Benjamin M. Ampel

Assistant Professor in Computer Information Systems and Director, Center for CyberAI Research (CCAIR)