Cyber Ranges (CRs) have emerged as prominent platforms for cybersecurity training and education, especially for Critical Infrastructure (CI) sectors that face rising cyber threats. One way to address these threats is through hands-on exercises that bridge IT and OT domains to improve defensive readiness. However, consistently evaluating whether a CR platform is suitable and effective remains a challenge. This paper proposes an evaluation framework for CRs, emphasizing mission-critical settings by using a multi-criteria decision-making approach. We define a set of evaluation criteria that capture technical fidelity, training and assessment capabilities, scalability, usability, and other relevant factors. To weight and aggregate these criteria, we employ the Analytic Hierarchy Process (AHP), supported by a simulated panel of multidisciplinary experts implemented through a Large Language Model (LLM). This LLM-assisted expert reasoning enables consistent and reproducible pairwise comparisons across criteria without requiring direct expert convening. The framework's output equals quantitative scores that facilitate objective comparison of CR platforms and highlight areas for improvement. Overall, this work lays the foundation for a standardized and explainable evaluation methodology to guide both providers and end-users of CRs.

翻译：网络靶场已成为网络安全培训与教育的重要平台，尤其对于面临日益增长网络威胁的关键基础设施领域。应对这些威胁的一种有效途径是通过融合信息技术与运营技术的实践演练来提升防御准备能力。然而，如何持续评估网络靶场平台的适用性与有效性仍面临挑战。本文提出一种面向网络靶场的评估框架，通过采用多准则决策方法，重点关注任务关键型应用场景。我们定义了一套评估准则，涵盖技术保真度、培训与评估能力、可扩展性、可用性及其他相关因素。为确定这些准则的权重并进行综合评估，我们采用层次分析法，并借助大语言模型构建的多学科专家模拟小组提供支持。这种基于大语言模型的专家推理机制，能够在无需直接召集专家的情况下，实现跨准则的一致性、可复现的成对比较。该框架最终输出量化评分，有助于实现网络靶场平台的客观比较并明确改进方向。总体而言，本研究为建立标准化、可解释的网络靶场评估方法奠定了基础，可为网络靶场提供商及终端用户提供指导。