A Deep and Scalable Unsupervised Machine Learning System for Cyber-Attack Detection in Large-Scale Smart Grids

A Deep and Scalable Unsupervised Machine Learning System for Cyber-Attack Detection in Large-Scale Smart Grids

Smart grid technology increases reliability, security, and efficiency of the electrical grids. However, its strong dependencies on digital communication technology bring up new vulnerabilities that need to be considered for efficient and reliable power distribution. In this paper, an unsupervised an...

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Bibliographic Details
Main Authors: Hadis Karimipour, Ali Dehghantanha, Reza M. Parizi, Kim-Kwang Raymond Choo, Henry Leung
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Anomaly
cyber-attack
smart grid
statistical property
machine learning
unsupervised learning
Online Access:https://ieeexplore.ieee.org/document/8727539/

Internet

https://ieeexplore.ieee.org/document/8727539/

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