Security Estimation of Stochastic Complex Networks under Stackelberg Game Framework
Li Li, Huixia Zhang, Huan Yang, Xijuan Wang · 2018
The paper concentrates on the power control problem of security estimation for stochastic complex networks subject to malicious attacks. A recursive unbiased minimum variance state estimation algorithm is used to estimate the states for every node with stochastic coupling states. The attacker is assumed to be a smart jammer who can quickly learn the transmission power of sensors and adaptively adjust its transmission power to maximize the damaging effect. A Stackelberg game formulation is established to describe interactive decision of smart sensors and the smart attacker. The optimal power control strategy for the sensors is derived. Finally, an example is provided to demonstrate the effectiveness of the proposed technique.