Human-Centered Threat Modeling in Practice: Lessons, Challenges, and Paths Forward

• URL: http://arxiv.org/abs/2511.13781v1
• Date: Sun, 16 Nov 2025 03:03:41 GMT
• Title: Human-Centered Threat Modeling in Practice: Lessons, Challenges, and Paths Forward
• Abstract summary: We conduct 23 semi-structured interviews with researchers to examine the state of human-centered threat modeling (HCTM)<n>We find that HCTM is not a prescriptive process but a set of evolving practices shaped by relationships with participants, disciplinary backgrounds, and institutional structures.<n>We conclude by identifying opportunities to advance HCTM through shared infrastructure, broader recognition of diverse contributions, and stronger mechanisms for translating findings into policy, design, and societal change.
• Score: 8.374213820742199
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Human-centered threat modeling (HCTM) is an emerging area within security and privacy research that focuses on how people define and navigate threats in various social, cultural, and technological contexts. While researchers increasingly approach threat modeling from a human-centered perspective, little is known about how they prepare for and engage with HCTM in practice. In this work, we conduct 23 semi-structured interviews with researchers to examine the state of HCTM, including how researchers design studies, elicit threats, and navigate values, constraints, and long-term goals. We find that HCTM is not a prescriptive process but a set of evolving practices shaped by relationships with participants, disciplinary backgrounds, and institutional structures. Researchers approach threat modeling through sustained groundwork and participant-centered inquiry, guided by values such as care, justice, and autonomy. They also face challenges including emotional strain, ethical dilemmas, and structural barriers that complicate efforts to translate findings into real-world impact. We conclude by identifying opportunities to advance HCTM through shared infrastructure, broader recognition of diverse contributions, and stronger mechanisms for translating findings into policy, design, and societal change.

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