Detecting Stealthy False Data Injection Using Machine Learning in Smart Grid

• Published in: IEEE systems journal Vol. 11; no. 3; pp. 1644 - 1652
• Main Authors: Esmalifalak, Mohammad, Liu, Lanchao, Nguyen, Nam, Zheng, Rong, Han, Zhu
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Anomaly detection; bad data detection (BDD); Boolean functions; Cybersecurity; Data structures; Machine learning; Measurement methods; power system state estimation; Principal component analysis; Principal components analysis; Residential energy; Smart grid; Smart grids; State estimation; Support vector machines; support vector machines (SVMs); System effectiveness; Training; Transmission line measurements

Aging power industries, together with the increase in demand from industrial and residential customers, are the main incentive for policy makers to define a road map to the next-generation power system called the smart grid. In the smart grid, the overall monitoring costs will be decreased, but at t...