Stackelberg Games for Blockchain Malware Detection: A Multi-Dimensional Viability Framework

While blockchain technology offers promising solutions for malware detection through decentralized signature sharing, the strategic interactions between malicious actors and security agencies create complex adversarial dynamics that traditional viability assessment methods fail to capture. This paper presents a novel game-theoretic framework that combines multi-dimensional viability analysis with Stackelberg equilibrium theory to evaluate blockchain-based malware detection systems. We model the interaction between certified security agencies (leaders) and potential attackers (followers) as a two-stage Stackelberg game, where agencies strategically choose their signature publication policies while attackers respond by optimizing their malware deployment strate-gies. Our main contribution is the Blockchain Security Equilibrium Theorem, which proves the existence and uniqueness of Nash-Stackelberg equilibrium in this adversarial setting. Through theoretical analysis and empiri-cal validation using the original multi-dimensional framework data, we demonstrate that our framework provides more accurate viability predictions compared to existing methodologies, offering critical insights for designing robust blockchain-based security solutions.