Dynamic game modeling and DNAS

Security is of paramount importance to the Internet of Vehicles (IoV), leading to the proposal of the Dual-S architecture integrating functional safety and cybersecurity. However, complex resource competition, collaborative interactions, irreconcilable external adversarial interactions, and mutual outcome transmission across these two security levels lack a unified descriptive and analytical framework. To address this gap, we propose DNAS2–a Dual-Nature Alliance Security and Strategy Framework for IoV security–based on mainstream game theory, which consists of two interconnected core modules: in the Internal Cooperative Game Module, we formalize the Dual-S Alliance with collective rationality prioritized over individual interests, propose an equilibrium solution method for coalition benefit allocation, and prove that this method can drive the endogenous security system toward Pareto optimality; in the External Non-Cooperative Attack-Defense Game Module, we construct a model incorporating dynamic strategy evolution and information asymmetry in attack-defense confrontations, derive equilibrium solutions, and provide a mathematical basis for optimal defense strategy formulation and payoff prediction. The unified analytical tool we propose supports the optimization of IoV security schemes, and future work will focus on model refinement, exploring its applications in evolutionary game scenarios, and promoting its engineering implementation.