Collaborative Intelligence: Topic Modelling of Large Language Model use in Live Cybersecurity Operations
Martin Lochner, Keegan Keplinger

TL;DR
This study analyzes how cybersecurity SOC operators use GPT-4 in live operations, revealing that they mainly leverage LLMs to understand complex texts, which can inform the development of collaborative tools.
Contribution
It introduces a novel topic modeling workflow to analyze LLM usage in cybersecurity operations, providing insights into user behavior and workflow integration.
Findings
SOC operators primarily use LLMs for understanding complex text strings.
Approximately 40% of LLM usage relates to interpreting complex commands.
The study suggests designing collaborative LLM tools to support SOC workflows.
Abstract
Objective: This work describes the topic modelling of Security Operations Centre (SOC) use of a large language model (LLM), during live security operations. The goal is to better understand how these specialists voluntarily use this tool. Background: Human-automation teams have been extensively studied, but transformer-based language models have sparked a new wave of collaboration. SOC personnel at a major cybersecurity provider used an LLM to support live security operations. This study examines how these specialists incorporated the LLM into their work. Method: Our data set is the result of 10 months of SOC operators accessing GPT-4 over an internally deployed HTTP-based chat application. We performed two topic modelling exercises, first using the established BERTopic model (Grootendorst, 2022), and second, using a novel topic modeling workflow. Results: Both the BERTopic…
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