Qolomany Basheer, Calay Tristan J, Hossain Liaquat, Mulahuwaish Aos, Bou Abdo Jacques
Cyber Systems Department, University of Nebraska at Kearney, Kearney, NE 68849, USA.
School of Information Technology, University of Cincinnati, Cincinnati, OH 45221, USA.
Entropy (Basel). 2024 Apr 30;26(5):384. doi: 10.3390/e26050384.
Cyber competitions are usually team activities, where team performance not only depends on the members' abilities but also on team collaboration. This seems intuitive, especially given that team formation is a well-studied discipline in competitive sports and project management, but unfortunately, team performance and team formation strategies are rarely studied in the context of cybersecurity and cyber competitions. Since cyber competitions are becoming more prevalent and organized, this gap becomes an opportunity to formalize the study of team performance in the context of cyber competitions. This work follows a cross-validating two-approach methodology. The first is the computational modeling of cyber competitions using Agent-Based Modeling. Team members are modeled, in NetLogo, as collaborating agents competing over a network in a red team/blue team match. Members' abilities, team interaction and network properties are parametrized (inputs), and the match score is reported as output. The second approach is grounded in the literature of team performance (not in the context of cyber competitions), where a theoretical framework is built in accordance with the literature. The results of the first approach are used to build a causal inference model using Structural Equation Modeling. Upon comparing the causal inference model to the theoretical model, they showed high resemblance, and this cross-validated both approaches. Two main findings are deduced: first, the body of literature studying teams remains valid and applicable in the context of cyber competitions. Second, coaches and researchers can test new team strategies computationally and achieve precise performance predictions. The targeted gap used methodology and findings which are novel to the study of cyber competitions.
网络竞赛通常是团队活动,团队表现不仅取决于成员的能力,还取决于团队协作。这似乎是直观的,特别是考虑到团队组建在竞技体育和项目管理中是一个经过充分研究的学科,但不幸的是,在网络安全和网络竞赛的背景下,很少研究团队表现和团队组建策略。由于网络竞赛越来越普遍且有组织,这一差距成为在网络竞赛背景下将团队表现研究形式化的一个机会。这项工作采用了一种交叉验证的双方法方法论。第一种方法是使用基于智能体的建模对网络竞赛进行计算建模。在NetLogo中,团队成员被建模为在红队/蓝队比赛中通过网络进行竞争的协作智能体。成员能力、团队互动和网络属性被参数化(输入),比赛得分作为输出报告。第二种方法基于团队表现的文献(而非网络竞赛背景下的文献),在其中根据文献构建一个理论框架。第一种方法的结果用于使用结构方程建模构建一个因果推理模型。将因果推理模型与理论模型进行比较时,发现它们高度相似,这对两种方法都进行了交叉验证。得出了两个主要发现:第一,研究团队的文献主体在网络竞赛背景下仍然有效且适用。第二,教练和研究人员可以通过计算测试新的团队策略并实现精确的表现预测。所针对的差距采用了对网络竞赛研究来说新颖的方法和发现。