Data-driven FDI Attacks: A Stealthy Approach to Subvert SVM Detectors in Power System
Author:
Affiliation:
1. Kansas State University,The Mike Wiegers Department of Electrical and Computer Engineering,Manhattan,Kansas,United States,66506
2. Colorado State University,Department of Mathematics,Fort Collins,Colorado,United States,80523
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10215098/10215099/10215462.pdf?arnumber=10215462
Reference19 articles.
1. Load Margin Constrained Moving Target Defense against False Data Injection Attacks
2. Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration
3. Smart Grid Cyber Attacks Detection Using Supervised Learning and Heuristic Feature Selection
4. Detecting Stealthy False Data Injection Using Machine Learning in Smart Grid
5. Voltage Stability Constrained Moving Target Defense Against Net Load Redistribution Attacks
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