As maritime operations increasingly depend on interconnected digital ecosystems, cyber incidents can propagate across maritime networks and degrade critical services. Strengthening strategic Cyber Situational Awareness (CSA) therefore requires training mechanisms that expose decision-makers to evolving attack dynamics, constrained resources, and the need to align actions with incident-response procedures. This paper introduces MARCIM-WG, a learning-oriented maritime cyberdefense wargame designed following the NATO wargaming methodology and implemented as a hybrid tabletop experience combining a physical board (tokens, indicators, and special cards) with analytically-assisted adjudication supported by a computational simulation model. The proposal is specified through High-Level Design (HLD) and Low-Level Design (LLD) specifications and instantiated in a fictional maritime cyber crisis scenario to enable structured decision cycles, friction, and measurable consequences. Validation combines (i) an operational scenario-based assessment under three configurations (pessimistic, neutral/most likely, optimistic) to verify decision sensitivity and outcome coherence, and (ii) a CSA competency and learning-outcome evaluation using a comparative design against an equivalent control group. Results show a +34.0 percentage-point improvement in the intervention group, with the largest gains in comprehension-related competencies.

翻译：摘要：随着海上行动日益依赖互联的数字生态系统，网络事件可能通过海上网络传播并降级关键服务。因此，强化战略级网络态势感知需要训练机制，使决策者暴露于不断演变的攻击动态、资源约束以及行动与事件响应程序对齐的需求中。本文提出MARCIM-WG，这是一种面向学习的海上网络防御兵棋推演方案，遵循北约兵棋推演方法论设计，并实现为混合式桌面推演体验——结合物理棋盘（标记物、指示物和特殊卡牌）与由计算仿真模型支持的辅助裁决分析。该方案通过高层设计（HLD）和低层设计（LLD）规范进行详细说明，并实例化于虚构的海上网络危机场景中，以实现结构化的决策循环、摩擦效应及可量化的后果。验证方式包括：（i）基于运行场景的三种配置（悲观、中性/最可能、乐观）评估，以验证决策敏感性和结果一致性；（ii）采用对比设计，通过与等效对照组比较进行CSA能力与学习成果评估。结果显示，干预组提升34.0个百分点，其中理解相关能力进步最为显著。