Fuzzy to Clear: Elucidating the Threat Hunter Cognitive Process and Cognitive Support Needs

2024-08-08

arXiv.org

AI Summary

This study addresses the lack of systematic understanding of threat hunters’ cognitive processes in cybersecurity. Through participatory observation and semi-structured interviews, we conducted a qualitative empirical investigation—yielding the first evidence-based cognitive evolution model for threat hunting. The model characterizes how analysts dynamically construct and iteratively refine mental models during real-world operations. From our data, we distilled 23 core human-factor requirements, which informed five actionable, human–machine collaboration design principles for security analytics tools. Our work bridges a critical gap in threat hunting human factors research and provides both a theoretical foundation and practical guidelines for developing next-generation, cognition-centered security analysis systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Humans and AI: Brain-Sensing and Analysis
• Search and Optimization: Metareasoning and Metaheuristics

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Web Mining and Content Analysis: Models for Web evolution
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

With security threats increasing in frequency and severity, it is critical that we consider the important role of threat hunters. These highly-trained security professionals learn to see, identify, and intercept security threats. Many recent works and existing tools in cybersecurity are focused on automating the threat hunting process, often overlooking the critical human element. Our study shifts this paradigm by emphasizing a human-centered approach to understanding the lived experiences of threat hunters. By observing threat hunters during hunting sessions and analyzing the rich insights they provide, we seek to advance the understanding of their cognitive processes and the tool support they need. Through an in-depth observational study of threat hunters, we introduce a model of how they build and refine their mental models during threat hunting sessions. We also present 23 themes that provide a foundation to better understand threat hunter needs and suggest five actionable design propositions to enhance the tools that support them. Through these contributions, our work enriches the theoretical understanding of threat hunting and provides practical insights for designing more effective, human-centered cybersecurity tools.

Problem

• Understanding threat hunters' cognitive processes
• Identifying support needs for threat hunters
• Designing human-centered cybersecurity tools

Innovation

• Human-centered threat hunting approach
• Observational study of cognitive processes
• Design propositions for cybersecurity tools