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Detecting smart meter false data attacks using hierarchical feature clustering and incentive weighted anomaly detection

Abstract:

Spot pricing is often suggested as a method of increasing demand-side flexibility in electrical power load. However, few works have considered the vulnerability of spot pricing to financial fraud via false data injection (FDI) style attacks. The authors consider attacks which aim to alter the consumer load profile to exploit intraday price dips. The authors examine an anomaly detection protocol for cyber-attacks that seek to leverage spot prices for financial gain. In this way the authors out...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1049/cps2.12057

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Oxford e-Research Centre
Role:
Author
ORCID:
0000-0002-1816-8333
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Oxford e-Research Centre
Oxford college:
Lady Margaret Hall
Role:
Author
ORCID:
0000-0001-7527-3407
Publisher:
Wiley
Journal:
IET Cyber-Physical Systems: Theory & Applications More from this journal
Volume:
8
Issue:
4
Pages:
257-271
Publication date:
2023-05-09
Acceptance date:
2023-04-12
DOI:
EISSN:
2398-3396
Language:
English
Keywords:
Pubs id:
1337202
Local pid:
pubs:1337202
Deposit date:
2023-04-12

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