Cybersecurity threat and risk analysis (RA) approaches are used to identify and mitigate security risks early-on in the software development life-cycle. Existing approaches automate only parts of the analysis procedure, leaving key decisions in identification, feasibility and risk analysis, and quality assessment to be determined by expert judgement. Therefore, in practice teams of experts manually analyze the system design by holding brainstorming workshops. Such decisions are made in face of uncertainties, leaving room for biased judgement (e.g., preferential treatment of category of experts). Biased decision making during the analysis may result in unequal contribution of expertise, particularly since some diversity dimensions (i.e., gender) are underrepresented in security teams. Beyond the work of risk perception of non-technical threats, no existing work has empirically studied the role of diversity in the risk analysis of technical artefacts. This paper proposes an experimental plan for identifying the key diversity factors in RA.