Deep learning-based multilabel classification for locational detection of false data injection attack in smart grids

• Published in: Electrical engineering Vol. 104; no. 1; pp. 259 - 282
• Main Authors: Mukherjee, Debottam, Chakraborty, Samrat, Ghosh, Sandip
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2022; Springer Nature B.V
• Subjects: Algorithms; Deep learning; Economics and Management; Electrical Engineering; Electrical Machines and Networks; Energy Policy; Engineering; Machine learning; Monitoring; Original Paper; Power Electronics; Real time; Smart grid; Smart grid technology; State estimation; Unstructured data; Deep learning; False data injection attack; Cybersecurity; Power system security; Smart grid; State estimation

With the recent advancement in smart grid technology, real-time monitoring of grid is utmost essential. State estimation-based solutions provide a critical tool in monitoring and control of smart grids. Recently there has been an increased focus on false data injection attacks which can circumvent t...