A survey on detection and localisation of false data injection attacks in smart grids

Abstract In the recent years, cyberattacks to smart grids are becoming more frequent. Among the many malicious activities that can be launched against smart grids, the False Data Injection (FDI) attacks have raised significant concerns from both academia and industry. FDI attacks can affect the (int...

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Main Authors: Muhammad Irfan, Alireza Sadighian, Adeen Tanveer, Shaikha J. Al‐Naimi, Gabriele Oligeri
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:IET Cyber-Physical Systems
Subjects:
Online Access:https://doi.org/10.1049/cps2.12093
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author Muhammad Irfan
Alireza Sadighian
Adeen Tanveer
Shaikha J. Al‐Naimi
Gabriele Oligeri
author_facet Muhammad Irfan
Alireza Sadighian
Adeen Tanveer
Shaikha J. Al‐Naimi
Gabriele Oligeri
author_sort Muhammad Irfan
collection DOAJ
description Abstract In the recent years, cyberattacks to smart grids are becoming more frequent. Among the many malicious activities that can be launched against smart grids, the False Data Injection (FDI) attacks have raised significant concerns from both academia and industry. FDI attacks can affect the (internal) state estimation process—critical for smart grid monitoring and control—thus being able to bypass conventional Bad Data Detection (BDD) methods. Hence, prompt detection and precise localisation of FDI attacks are becoming of paramount importance to ensure smart grids security and safety. Several papers recently started to study and analyse this topic from different perspectives and address existing challenges. Data‐driven techniques and mathematical modelling are the major ingredients of the proposed approaches. The primary objective is to provide a systematic review and insights into FDI attacks joint detection and localisation approaches considering that other surveys mainly concentrated on the detection aspects without detailed coverage of localisation aspects. For this purpose, more than 40 major research contributions were selected and inspected, while conducting a detailed analysis of the methodology and objectives in relation to the FDI attacks detection and localisation. Key findings of the identified papers were provided according to different criteria, such as employed FDI attacks localisation techniques, utilised evaluation scenarios, investigated FDI attack types, application scenarios, adopted methodologies and the use of additional data. Finally, open issues and future research directions were discussed.
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spelling doaj-art-54dbb526709b4aa9b4292c041ccbca822025-08-20T02:39:44ZengWileyIET Cyber-Physical Systems2398-33962024-12-019431333310.1049/cps2.12093A survey on detection and localisation of false data injection attacks in smart gridsMuhammad Irfan0Alireza Sadighian1Adeen Tanveer2Shaikha J. Al‐Naimi3Gabriele Oligeri4Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University, Qatar Foundation Doha QatarDivision of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University, Qatar Foundation Doha QatarDivision of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University, Qatar Foundation Doha QatarDivision of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University, Qatar Foundation Doha QatarDivision of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University, Qatar Foundation Doha QatarAbstract In the recent years, cyberattacks to smart grids are becoming more frequent. Among the many malicious activities that can be launched against smart grids, the False Data Injection (FDI) attacks have raised significant concerns from both academia and industry. FDI attacks can affect the (internal) state estimation process—critical for smart grid monitoring and control—thus being able to bypass conventional Bad Data Detection (BDD) methods. Hence, prompt detection and precise localisation of FDI attacks are becoming of paramount importance to ensure smart grids security and safety. Several papers recently started to study and analyse this topic from different perspectives and address existing challenges. Data‐driven techniques and mathematical modelling are the major ingredients of the proposed approaches. The primary objective is to provide a systematic review and insights into FDI attacks joint detection and localisation approaches considering that other surveys mainly concentrated on the detection aspects without detailed coverage of localisation aspects. For this purpose, more than 40 major research contributions were selected and inspected, while conducting a detailed analysis of the methodology and objectives in relation to the FDI attacks detection and localisation. Key findings of the identified papers were provided according to different criteria, such as employed FDI attacks localisation techniques, utilised evaluation scenarios, investigated FDI attack types, application scenarios, adopted methodologies and the use of additional data. Finally, open issues and future research directions were discussed.https://doi.org/10.1049/cps2.12093power system securitysecurity of datasmart power grids
spellingShingle Muhammad Irfan
Alireza Sadighian
Adeen Tanveer
Shaikha J. Al‐Naimi
Gabriele Oligeri
A survey on detection and localisation of false data injection attacks in smart grids
IET Cyber-Physical Systems
power system security
security of data
smart power grids
title A survey on detection and localisation of false data injection attacks in smart grids
title_full A survey on detection and localisation of false data injection attacks in smart grids
title_fullStr A survey on detection and localisation of false data injection attacks in smart grids
title_full_unstemmed A survey on detection and localisation of false data injection attacks in smart grids
title_short A survey on detection and localisation of false data injection attacks in smart grids
title_sort survey on detection and localisation of false data injection attacks in smart grids
topic power system security
security of data
smart power grids
url https://doi.org/10.1049/cps2.12093
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