Reward Based Metrics for Assessing the Effectiveness of Shuffled Based Moving Target Defense

Abstract

The research evaluates the effectiveness of shuffle-based Moving Target Defense (MTD) on host and network systems using a temporal graph-based security model, T-HARM. A novel dynamic security metric, the Reward-Based Metric (RBM), is introduced to assess the impact of MTD from the defender’s perspective, capturing changes in system resilience and attacker effort. The study involves implementing shuffle-based MTD techniques, defining and integrating the new metric with existing ones, and conducting simulation-based experiments to analyze security posture over time. The results show that the dynamic metric more accurately reflects real-time security changes, and that shuffle-based MTD significantly increases attack complexity and delays system compromise, thereby enhancing overall network defense.