Effectiveness Evaluation Method for Hybrid Defense of Moving Target Defense and Cyber Deception
Fangbo Hou, Fangrun Hou, Xiaodong Zang, Ziyang Hua, Zhang Liu, Zhe Wu · Computers · 2025
Moving Target Defense (MTD) has been proposed as a dynamic defense strategy to address the static and isomorphic vulnerabilities of networks. Recent research in MTD has focused on enhancing its effectiveness by combining it with cyber deception techniques. However, there is limited research on evaluating and quantifying this hybrid defence framework. Existing studies on MTD evaluation often overlook the deployment of deception, which can expand the potential attack surface and introduce additional costs. Moreover, a unified model that simultaneously measures security, reliability, and defense cost is lacking. We propose a novel hybrid defense effectiveness evaluation method that integrates queuing and evolutionary game theories to tackle these challenges. The proposed method quantifies the safety, reliability, and defense cost. Additionally, we construct an evolutionary game model of MTD and deception, jointly optimizing triggering and deployment strategies to minimize the attack success rate. Furthermore, we introduce a hybrid strategy selection algorithm to evaluate the impact of various strategy combinations on security, resource consumption, and availability. Simulation and experimental results demonstrate that the proposed approach can accurately evaluate and guide the configuration of hybrid defenses. Demonstrating that hybrid defense can effectively reduce the attack success rate and unnecessary overhead while maintaining Quality of Service (QoS).