Detection and Security Control for Supply Chain System Under FDI Attack

In modern supply chain system, the cyber layer and physical layer integrate the information and physical world, which are vulnerable to the network attack, and eventually leads to the design change of the production and supply chains. In this paper, based on the analysis of the cascade production process of the supply chain system, a partial form dynamic linearization nominal model is established by using the pseudo-partial derivative method and the data model of the sensor-controller (S-C) communication channel under the false data injection attack is studied. Then, a network attack detection estimator is designed and a time-varying residual threshold is given to judge whether an attack occurs or not. Considering that the parameter matrix and network attack in the data model are unknown and time-varying, they are estimated respectively using the input/output data of the system. Finally, a model free adaptive security control algorithm is designed to ensure that the inventory status of each enterprise node can track the ideal security inventory status when the supply chain system is under network attack. A simulation example is provided to verify the effectiveness of the proposed attack detection and security control algorithm.