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Prompt-Based Learning for Thread Structure Prediction in Cybersecurity Forums

Authors :
Kashihara, Kazuaki
Pal, Kuntal Kumar
Baral, Chitta
Trevino, Robert P
Publication Year :
2023

Abstract

With recent trends indicating cyber crimes increasing in both frequency and cost, it is imperative to develop new methods that leverage data-rich hacker forums to assist in combating ever evolving cyber threats. Defining interactions within these forums is critical as it facilitates identifying highly skilled users, which can improve prediction of novel threats and future cyber attacks. We propose a method called Next Paragraph Prediction with Instructional Prompting (NPP-IP) to predict thread structures while grounded on the context around posts. This is the first time to apply an instructional prompting approach to the cybersecurity domain. We evaluate our NPP-IP with the Reddit dataset and Hacker Forums dataset that has posts and thread structures of real hacker forums' threads, and compare our method's performance with existing methods. The experimental evaluation shows that our proposed method can predict the thread structure significantly better than existing methods allowing for better social network prediction based on forum interactions.<br />Comment: 16 pages, 7 figures, submitted to IntelliSys 2023

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2303.05400
Document Type :
Working Paper