Gaussian Process Learning for Distributed Sensor Networks under False Data Injection Attacks

• Published in: 2019 IEEE Conference on Dependable and Secure Computing (DSC) pp. 1 - 6
• Main Authors: Liu, Xiuming, Ngai, Edith
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2019
• Subjects: Distributed databases; Distributed Sensor Network; False Data Injection Attack; Gaussian processes; Hyper-Parameter Learning; Maximum likelihood estimation; Monitoring; Parameter estimation; Peer-to-peer computing; Spatial Gaussian Process; Task analysis

Distributed sensor networks are the backbone of many modern intelligent systems. The collected sensor data are fused and processed to learn the underlying model (such as the Gaussian process) of interested physical process, which serves as critical knowledge for the further decision making process....