CCTFv2: Modeling Cyber Competitions

Area of Science:

• Cybersecurity
• Computational Social Science
• Team Performance Studies

Background:

• Cyber competitions are increasingly prevalent, yet team performance and formation strategies are understudied in this domain.
• Existing research on team dynamics in sports and project management lacks direct application to cybersecurity contexts.
• A formal study of team performance is needed to optimize strategies for cyber competitions.

Purpose of the Study:

• To investigate and formalize the study of team performance within cyber competitions.
• To bridge the gap between general team performance literature and the specific domain of cybersecurity.
• To validate the applicability of established team theories to cyber competition environments.

Main Methods:

• Utilized Agent-Based Modeling (ABM) in NetLogo to computationally simulate cyber competitions.
• Modeled team members as collaborating agents with varying abilities and interaction levels within a network.
• Developed a theoretical framework from team performance literature and employed Structural Equation Modeling (SEM) for causal inference, cross-validating with ABM results.

Main Results:

• ABM simulations demonstrated that team collaboration is a critical factor in cyber competition outcomes.
• SEM analysis confirmed a high resemblance between the computational model and the theoretical framework.
• The study successfully cross-validated computational and theoretical approaches to understanding team performance in cyber competitions.

Conclusions:

• Established theories of team performance are directly applicable and valid within the context of cyber competitions.
• Computational modeling offers a powerful tool for coaches and researchers to test novel team strategies and predict performance accurately.
• This research introduces novel methodology and findings to the field of cyber competition analysis.