Document Type
Article
Publication Date
2025
Abstract
Open-Source Intelligence (OSINT) is often regarded as a critical component for cybersecurity intelligence gathering to secure cyber infrastructures. As Artificial Intelligence (AI) and social media progress and become more commonplace, we have the unique opportunity to collect and analyze information from social media in real time. In this paper, we propose an AI-based framework for automatically filtering the Twitter stream for cybersecurity information, analyzing the natural language to aggregate the tweets around specific cybersecurity events, and certifying the information. The system's applications range from discovering events security operators may not have been aware of to helping operators investigate on-going events affecting their systems. Furthermore, we propose a method to identify the network protocols associated with software vulnerabilities based on Twitter data, leveraging the aforementioned framework. This method can further aid operators in understanding the exploitability of vulnerabilities (e.g., whether exploitation is already blocked by firewall rules) and making mitigation measures (e.g., adding a firewall rule to block exploitation). Evaluations show the effectiveness of our solutions.
Citation
Dale, D. S., Mcclanahan, K., Elder, W. S., & Li, Q. (2025). Twitter-Based OSINT for Cyber Event Analytics. IEEE Access, 13 https://doi.org/10.1109/ACCESS.2025.3607382
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Keywords
AI, cybersecurity, OSINT
Comments
Web of Science
IEEE