Deep Neural Network-Based Stealthy False Data Injection Attack Detection on Distributed Energy Resources Integrated Systems

Can Gürkan, Necati Aksoy, V. M.Istemihan Genc

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

State estimation is a critical process for ensuring the secure and reliable operation of power systems by determining the operating state of a system based on available measurements. Recent studies indicate that the state estimation process can be compromised by False Data Injection Attacks (FDIA). These attacks involve injecting attack vectors into compromised measurements to evade bad data detection methods. While conventional state estimation is already susceptible to such attacks, the increasing penetration of distributed energy resources (DERs) has exacerbated the system's vulnerability to cyber-attacks. In this paper, we propose a deep learning-based FDIA detection method to identify cyber-attacks in power systems with a high penetration rate of DERs. We compare this method with widely-used classification algorithms for detecting anomalies in state estimation and measurements. The proposed approaches are evaluated using historical load data from the New York Independent System Operator (NYISO) on two IEEE test systems: the 30-bus and 57-bus systems. The methods are tested under various DER contributions and noise levels. Results demonstrate the efficacy of the proposed methods in detecting FDIAs in power systems with varying levels of DER penetration.

Original languageEnglish
Title of host publication2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024
EditorsAydin Cetin, Tulay Yildirim, Bulent Bolat
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350379433
DOIs
Publication statusPublished - 2024
Event2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 - Ankara, Turkey
Duration: 16 Oct 202418 Oct 2024

Publication series

Name2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

Conference

Conference2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024
Country/TerritoryTurkey
CityAnkara
Period16/10/2418/10/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • Cyber-security
  • deep learning
  • false data injection attack
  • machine learning
  • smart grids
  • state estimation

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