| Title | Attacks Detection and Security Control Against False Data Injection Attacks Based on Interval Type-2 Fuzzy System |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Chen, Yuhang, Long, Yue, Li, Tieshan |
| Conference Name | IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society |
| Keywords | composability, CPS modeling, Cyber physical system, Data models, FDI attacks, Industrial electronics, IT2 Fuzzy System, Linear systems, Metrics, nonlinear systems, Observers, Oscillators, pubcrawl, resilience, Resiliency, Robust Fuzzy Extended States Observer, security, simulation |
| Abstract | This paper is concered with the nonlinear cyber physical system (CPS) with uncertain parameters under false data injection (FDI) attacks. The interval type-2 (IT2) fuzzy model is utilized to approximate the nonlinear system, then the nonlinear system can be represented as a convex combination of linear systems. To detect the FDI attacks, a novel robust fuzzy extended state observer with H preformance is proposed, where the fuzzy rules are utilized to the observer to estimate the FDI attacks. Utilizing the observation of the FDI attacks, a security control scheme is proposed in this paper, in which a compensator is designed to offset the FDI attacks. Simulation examples are given to illustrate the effecitveness of the proposed security scheme. |
| DOI | 10.1109/IECON49645.2022.9968628 |
| Citation Key | chen_attacks_2022 |
Attacks Detection and Security Control Against False Data Injection Attacks Based on Interval Type-2 Fuzzy System