MARCIM-WG: A cyber wargame proposal based on math modeling applied in a naval scenario
2026-06-10 • Cryptography and Security
Cryptography and Security
AI summaryⓘ
The authors created MARCIM-WG, a game to help people learn how to defend against cyberattacks in maritime settings. The game uses a mix of physical pieces and computer simulations to mimic real-world cyber crisis situations. It was tested to see if playing the game helps improve understanding and decision-making in these complex scenarios. The study found that participants who played MARCIM-WG showed much better skills, especially in understanding cyber threats. This suggests the game is a useful tool for training in maritime cyber defense.
Cyber Situational AwarenessMaritime CybersecurityWargamingNATO Wargaming MethodologyHybrid Tabletop SimulationDecision-Making TrainingIncident-Response ProceduresOperational Scenario AssessmentLearning OutcomesSimulation Model
Authors
Diego Cabuya-Padilla, Daniel Díaz-López, Carlos Castaneda-Marroquín
Abstract
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.