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An Integrated Detection System Against False Data Injection Attacks in the Smart Grid



Wei Yu, David W. Griffith, Linqiang Ge, Sulabh Bhattarai, Nada T. Golmie


The smart grid is a new type of power grid that will use the advanced communication network technologies to support more efficient energy transmission and distribution. The grid infrastructure was designed for reliability; but security, especially against cyber threats, is also a critical need. In particular, an adversary can inject false data to disrupt the system operation. In this paper, we develop a system that integrates two detection techniques. We adopt anomaly-based detection to detect strong attacks that feature the injection of large amounts of spurious measurement data in a very short time. We integrate the anomaly detection with a watermarking-based detection scheme that prevents more stealthy attacks that involve subtle manipulation of the measurement data. We conduct the theoretical analysis to derive the close formulae for investigating the effectiveness of our proposed detection techniques. Our experimental data shows that our integrated detection system can accurately detect both strong and stealthy attacks
Security and Communication Networks
Created March 4, 2014, Updated February 19, 2017