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Detalhes Referência

Tipo
Artigos em Revista

Tipo de Documento
Artigo Completo

Título
Artificial Neural Network-Based Stealth Attack on Battery Energy Storage Systems

Participantes na publicação
Marco Pasetti (Author)
Paolo Ferrari (Author)
Paolo Bellagente (Author)
Emiliano Sisinni (Author)
Alan Oliveira de Sa (Author)
Dep. Informática
Charles B. do Prado (Author)
Rodrigo P. David (Author)
Raphael C. S. Machado (Author)

Resumo
As the number of installed Battery Energy Storage Systems (BESSs) increases, the concerns related to possible cyber-attacks to these systems rise accordingly. The most of BESS owners knows their systems may be vulnerable, but they often consider only denial of service attacks in their risk assessment. Unfortunately, other, subtler and more dangerous attacks exist. In this paper we show that a stealth attack to BESSs can be performed by applying a Man-in-the-Middle (MitM) approach. The aim of the attack is to stealthily manage the physical system by hiding the actual behavior of the system to its supervisory controller. In this case the attacker would be able to: (i) degrade the BESS by reducing its expected lifetime, (ii) produce economic losses for the prosumer, and (iii) affect the security and stability of the grid. The feasibility of the attack is demonstrated by providing an example of a stealth MitM attack on a real BESS coupled with a photovoltaic power plant. The proposed case study demonstrates that such attack can be performed without being discovered by end-users and shows that its effects can be severe. Finally, possible strategies to avoid or detect such kind of attack are discussed.

Data de Publicação
2021

Suporte
IEEE Transactions on Smart Grid

Identificadores da Publicação
ISSN - 1949-3053

Editora
Institute of Electrical and Electronics Engineers (IEEE)

Número de Páginas
1
Página Inicial
1
Página Final
1

Identificadores do Documento
DOI - https://doi.org/10.1109/tsg.2021.3102833
URL - http://dx.doi.org/10.1109/tsg.2021.3102833

Identificadores de Qualidade
SCIMAGO Q1 (2020) - 3.571 - Computer Science (miscellaneous)

Keywords
Battery energy storage system (BESS) cyber-security man-in-the-middle (MitM) stealth attack cyber-physical bess modelling.


Exportar referência

APA
Marco Pasetti, Paolo Ferrari, Paolo Bellagente, Emiliano Sisinni, Alan Oliveira de Sa, Charles B. do Prado, Rodrigo P. David, Raphael C. S. Machado, (2021). Artificial Neural Network-Based Stealth Attack on Battery Energy Storage Systems. IEEE Transactions on Smart Grid, 1-1. ISSN 1949-3053. eISSN . http://dx.doi.org/10.1109/tsg.2021.3102833

IEEE
Marco Pasetti, Paolo Ferrari, Paolo Bellagente, Emiliano Sisinni, Alan Oliveira de Sa, Charles B. do Prado, Rodrigo P. David, Raphael C. S. Machado, "Artificial Neural Network-Based Stealth Attack on Battery Energy Storage Systems" in IEEE Transactions on Smart Grid, pp. 1-1, 2021. 10.1109/tsg.2021.3102833

BIBTEX
@article{52297, author = {Marco Pasetti and Paolo Ferrari and Paolo Bellagente and Emiliano Sisinni and Alan Oliveira de Sa and Charles B. do Prado and Rodrigo P. David and Raphael C. S. Machado}, title = {Artificial Neural Network-Based Stealth Attack on Battery Energy Storage Systems}, journal = {IEEE Transactions on Smart Grid}, year = 2021, pages = {1-1}, }