GTI-mSEMP Framework Models Malware with Attacker-Defender Game Theory

Researchers Shadeeb Hossain and Kristopher Wilson have introduced the GTI-mSEMP (Game-Theory-Integrated Modified Multi-Wireless Sensor Epidemic Malware Propagation) framework, designed to model the dynamic spread of automated, multi-vector malware in heterogeneous, resource-constrained cyber-physical networks. Traditional epidemiological models treat security defenses as static parameters, failing to account for the asymmetric strategic maneuvers between attackers and defenders. GTI-mSEMP fills this gap by integrating game theory, allowing the framework to simulate how offensive and defensive scaling vectors influence malware propagation in real time. The paper analyzes three operational regimes: Balanced Matchup, where attacker and defender capabilities are roughly equal; Exploit Surge, highlighting scenarios where offensive vectors dominate; and Hardened Defense, demonstrating robust defensive advantages.

The framework's numerical simulation results capture transient dynamics of Susceptible (S) and Recovered (R) node populations, showing how epidemic curves shift under different strategic conditions. This provides a rigorous mathematical foundation for predicting localized node states in highly adversarial network environments. As malware continues to evolve with autonomous, multi-vector behaviors, GTI-mSEMP offers cybersecurity professionals a powerful tool to evaluate dynamic propagation scenarios, optimize defense strategies, and anticipate network vulnerabilities before they are exploited. The 14-page paper is available on arXiv and marks a significant step toward more adaptive threat modeling.