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Publication detail
KURUKURU, V. KHAN, M. SAHOO, S.
Original Title
Cybersecurity in Power Electronics Using Minimal Data - A Physics-Informed Spline Learning Approach
Type
journal article in Web of Science
Language
English
Original Abstract
Cyberattacks can be strategically counterfeited to replicate grid faults, thereby manipulating the protection system and leading to accidental disconnection of grid-tied converters. To prevent such setbacks, we propose a physics-informed spline learning approach-based anomaly diagnosis mechanism to distinguish between both events using minimal data for the first time in the realm of power electronics. This methodology not only provides compelling accuracy with limited data, but also reduces the training and computational resources significantly. We validate its effectiveness and accuracy under experimental conditions to conclude how data availability problem can be handled.
Keywords
Splines (mathematics); Cyberattack; Voltage measurement; Mathematical models; Physics; Circuit faults; Current measurement; Anomaly diagnosis; artificial intelligence; cyberattacks; photovoltaic inverters
Authors
KURUKURU, V.; KHAN, M.; SAHOO, S.
Released
8. 6. 2022
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Location
PISCATAWAY
ISBN
0885-8993
Periodical
IEEE TRANSACTIONS ON POWER ELECTRONICS
Year of study
37
Number
11
State
United States of America
Pages from
12938
Pages to
12943
Pages count
6
URL
https://ieeexplore.ieee.org/abstract/document/9791853
BibTex
@article{BUT178406, author="V S Bharath {Kurukuru} and Mohammed Ali {Khan} and Subham {Sahoo}", title="Cybersecurity in Power Electronics Using Minimal Data - A Physics-Informed Spline Learning Approach", journal="IEEE TRANSACTIONS ON POWER ELECTRONICS", year="2022", volume="37", number="11", pages="12938--12943", doi="10.1109/TPEL.2022.3180943", issn="0885-8993", url="https://ieeexplore.ieee.org/abstract/document/9791853" }