Detail publikace

Cybersecurity in Power Electronics Using Minimal Data - A Physics-Informed Spline Learning Approach

KURUKURU, V. KHAN, M. SAHOO, S.

Originální název

Cybersecurity in Power Electronics Using Minimal Data - A Physics-Informed Spline Learning Approach

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Splines (mathematics); Cyberattack; Voltage measurement; Mathematical models; Physics; Circuit faults; Current measurement; Anomaly diagnosis; artificial intelligence; cyberattacks; photovoltaic inverters

Autoři

KURUKURU, V.; KHAN, M.; SAHOO, S.

Vydáno

8. 6. 2022

Nakladatel

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Místo

PISCATAWAY

ISSN

0885-8993

Periodikum

IEEE TRANSACTIONS ON POWER ELECTRONICS

Ročník

37

Číslo

11

Stát

Spojené státy americké

Strany od

12938

Strany do

12943

Strany počet

6

URL

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"
}