We model a vehicle equipped with an autonomous cyber-defense system in addition to its inherent physical resilience features. When attacked, this ensemble of cyber-physical features (i.e., ``bonware'') strives to resist and recover from the performance degradation caused by the malware's attack. We model the underlying differential equations governing such attacks for piecewise linear characterizations of malware and bonware, develop a discrete time stochastic model, and show that averages of instantiations of the stochastic model approximate solutions to the continuous differential equation. We develop a theory and methodology for approximating the parameters associated with these equations.

翻译：我们对配备自主网络防御系统的车辆进行建模，该系统额外具有其固有的物理弹性特征。当遭受攻击时，这种网络-物理特征集合（即"防御件"）致力于抵抗恶意软件攻击导致的性能下降，并从中恢复。我们针对恶意软件与防御件的分段线性特征，对支配此类攻击的底层微分方程进行建模；开发了一种离散时间随机模型，并证明了该随机模型多次实例化的平均值可近似连续微分方程的解。我们建立了一套理论和方法来近似这些方程的相关参数。