论文标题
虚假数据注入攻击下的弹性分布式资源分配算法
Resilient distributed resource allocation algorithm under false data injection attacks
论文作者
论文摘要
提出了一种弹性分布式算法来解决遭受错误数据注入（FDI）攻击的一阶非线性多机构系统的分布式资源分配问题。智能攻击者将虚假数据注射到代理的执行器和传感器中，以便根据受损的控制输入和交互式信息执行算法。攻击者的目的是使多代理系统变得不稳定，并导致代理人从最佳资源分配中的决策偏差。首先，我们分析了FDI攻击下分布式资源分配算法的鲁棒性。然后，未知的非线性项和注入代理中注入的错误数据被认为是扩展状态，可以通过扩展状态观察者估算。该估计用于反馈控制以抑制FDI攻击的效果。提出了基于扩展状态观察者的弹性分布式资源分配算法，以确保它可以收敛到最佳分配，而无需任何有关攻击者性质的信息。给出一个示例来说明结果。
A resilient distributed algorithm is proposed to solve the distributed resource allocation problem of a first-order nonlinear multi-agent system who is subject to false data injection (FDI) attacks. An intelligent attacker injects false data into agents' actuators and sensors such that agents execute the algorithm according to the compromised control inputs and interactive information. The goal of the attacker is to make the multi-agent system to be unstable and to cause the deviance of agents' decisions from the optimal resource allocation. At first, we analyze the robustness of a distributed resource allocation algorithm under FDI attacks. Then, the unknown nonlinear term and the false data injected in agents are considered as extended states which can be estimated by extended state observers. The estimation was used in the feedback control to suppress the effect of the FDI attacks. A resilient distributed resource allocation algorithm based on the extended state observer is proposed to ensure that it can converge to the optimal allocation without requiring any information about the nature of the attacker. An example is given to illustrate the results.
