HAL CCSD
Stealth Attacks on the Smart Grid
Sun, Ke
Esnaola, Iñaki
Perlaza, Samir
Vincent Poor, Harold
Department of Automatic Control and Systems Engineering [ Sheffield] (ACSE) ; University of Sheffield [Sheffield]
Department of Electrical and Computer Engineering [Princeton] (ECE) ; Princeton University
Network Engineering and Operations (NEO ) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
International audience
ISSN: 1949-3053
EISSN: 1949-3061
IEEE Transactions on Smart Grid
Institute of Electrical and Electronics Engineers
hal-01857366
https://inria.hal.science/hal-01857366
https://inria.hal.science/hal-01857366v2/document
https://inria.hal.science/hal-01857366v2/file/SEPP_TSG_18.pdf
https://inria.hal.science/hal-01857366
IEEE Transactions on Smart Grid, 2020, ⟨10.1109/TSG.2019.2935353⟩
DOI: 10.1109/TSG.2019.2935353
info:eu-repo/semantics/altIdentifier/doi/10.1109/TSG.2019.2935353
en
Information-Theoretic Security
Mutual Information
Probability of Detection
Data Injection Attacks
Stealth Attacks
[MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT]
[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT]
[SPI.NRJ]Engineering Sciences [physics]/Electric power
info:eu-repo/semantics/article
Journal articles
Random attacks that jointly minimize the amount of information acquired by the operator about the state of the grid and the probability of attack detection are presented. The attacks minimize the information acquired by the operator by minimizing the mutual information between the observations and the state variables describing the grid. Simultaneously, the attacker aims to minimize the probability of attack detection by minimizing the Kullback-Leibler (KL) divergence between the distribution when the attack is present and the distribution under normal operation. The resulting cost function is the weighted sum of the mutual information and the KL divergence mentioned above. The trade-off between the probability of attack detection and the reduction of mutual information is governed by the weighting parameter on the KL divergence term in the cost function. The probability of attack detection is evaluated as a function of the weighting parameter. A sufficient condition on the weighting parameter is given for achieving an arbitrarily small probability of attack detection. The attack performance is numerically assessed on the IEEE 30-Bus and 118-Bus test systems.
2020-03-01
info:eu-repo/semantics/OpenAccess