Data-driven detection and identification of IoT-enabled load-altering attacks in power grids

Data-driven detection and identification of IoT-enabled load-altering attacks in power grids

Advances in edge computing are powering the development and deployment of Internet of Things (IoT) systems to provide advanced services and resource efficiency. However, large-scale IoT-based load-altering attacks (LAAs) can seriously impact power grid operations, such as destabilising the grid'...

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Bibliographic Details
Main Authors: Jahangir, H. (Author), Lakshminarayana, S. (Author), Maple, C. (Author), Poor, H.V (Author), Sthapit, S. (Author)
Format: Article
Language:English
Published: John Wiley and Sons Inc 2022
Subjects:
Compromised nodes
Control loop
Data driven
Detection and identifications
Edge computing
Electric power system control
Electric power transmission networks
Grid control
Internet of things
Large scale Internet
Neural-networks
Parameter estimation
Power grid operations
Resource efficiencies
Smart power grids
Support vector machines
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