Traditional Qualitative Methodology in an Innovative Setting: Cybercrime Research on Adversarial Decision-Making, Behavior, and Group Dynamics

• In Event: Deconstructing Research Silences through Qualitative Research

Abstract

Cybercrime, specifically adversarial decision-making, behavior, and group dynamics, are topics that are very difficult to qualitatively study within a Criminological discipline. One platform to utilize is a Red team versus Blue team (RvB) cybersecurity exercise, which involves the former attacking and the latter defending its system and network against the attack. While these have been extensively used for educational and training purposes in technical disciplines, the Criminological field has been slow to embrace these in research. This paper presents findings on adversarial group dynamics, behavior, and decision-making from four different RvB case studies that employed traditional qualitative methods of interviews and observations. It highlights (i) the challenges of conducting qualitative research in dynamic cyber-settings, (ii) the mechanisms of feedback-revision loops to improve data collection instruments, and (iii) the implications for generalizability and transferability.

Authors

• Brian Singer, Temple University

• Nicholas Masceri, Temple University

• Aunshul Rege, Temple University