TY - GEN
T1 - False data injection attacks against low voltage distribution systems
AU - Radoglou-Grammatikis, Panagiotis
AU - Dalamagkas, Christos
AU - Lagkas, Thomas
AU - Zafeiropoulou, Magda
AU - Atanasova, Maria
AU - Zlatev, Pencho
AU - Boulogeorgos, Alexandros-Apostolos A.
AU - Argyriou, Vasileios
AU - Markakis, Evangelos K.
AU - Moscholios, Ioannis
AU - Sarigiannidis, Panagiotis
N1 - Organising Body: IEEE
PY - 2023/1/11
Y1 - 2023/1/11
N2 - The transformation of the conventional electrical grid into a digital ecosystem brings significant benefits, such as two-way communication between energy consumers and utilities, self-monitoring and pervasive controls. However, the advent of the smart electrical grid raises severe cybersecurity and privacy concerns, given the presence of legacy systems and communications protocols. This paper focuses on False Data Injection (FDI) cyberattacks against a low-voltage distribution system, taking full advantage of Man In The Middle (MITM) actions. The first cyberattack targets the communication between a smart meter and an Active Distribution Management System (ADMS), while the second FDI cyberattack targets the communication between a smart inverter and ADMS. In both cases, the cyberattacks affect the operation of the distribution transformer, thus resulting in devastating consequences. Moreover, this paper provides an Artificial Intelligence (AI)-based Intrusion Detection System (IDS), detecting and mitigating the above cyberattacks in a timely manner. The evaluation results demonstrate the efficiency of the proposed IDS.
AB - The transformation of the conventional electrical grid into a digital ecosystem brings significant benefits, such as two-way communication between energy consumers and utilities, self-monitoring and pervasive controls. However, the advent of the smart electrical grid raises severe cybersecurity and privacy concerns, given the presence of legacy systems and communications protocols. This paper focuses on False Data Injection (FDI) cyberattacks against a low-voltage distribution system, taking full advantage of Man In The Middle (MITM) actions. The first cyberattack targets the communication between a smart meter and an Active Distribution Management System (ADMS), while the second FDI cyberattack targets the communication between a smart inverter and ADMS. In both cases, the cyberattacks affect the operation of the distribution transformer, thus resulting in devastating consequences. Moreover, this paper provides an Artificial Intelligence (AI)-based Intrusion Detection System (IDS), detecting and mitigating the above cyberattacks in a timely manner. The evaluation results demonstrate the efficiency of the proposed IDS.
KW - Computer science and informatics
U2 - 10.1109/GLOBECOM48099.2022.10000880
DO - 10.1109/GLOBECOM48099.2022.10000880
M3 - Conference contribution
SN - 9781665435413
T3 - IEEE Conference on Global Communications (GLOBECOM)
SP - 1856
EP - 1861
BT - 2022 IEEE Global Communications Conference (GLOBECOM)
PB - Institute of Electrical and Electronics Engineers
T2 - 2022 IEEE Global Communications Conference (GLOBECOM)
Y2 - 4 December 2022 through 8 December 2022
ER -