Enhanced Locational FDIA Detection in Smart Grids: A Scalable Distributed Framework

Maymouna Ez Eddin, Mohamed Massaoudi, Mohammad Shadmand, Mohamed Abdallah

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

Abstract

Locational detection of the false data injection attack (FDIA) is essential for smart grid cyber-security. However, the FDIA detection techniques often falter in scalability as power network complexity increases. To address the research gap, this paper introduces an innovative distributed framework for locational FDIA detection that optimizes both performance and scalability. The proposed framework initially partitions the power grid using the improved Louvain community detection algorithm. The proposed solution utilizes the Electrical Functional Strength (EFS) matrix and power supply modularity. Subsequently, a dedicated multi-label one-dimensional convolutional neural network model (1D CNN) locational detector is designed for each derived cluster. The proposed methodology is designed to increase detection accuracy and enhance the scalability of the model. This is achieved by reducing training and detection times, as well as lowering memory requirements, compared to traditional centralized approaches. The effectiveness of the proposed framework is validated through simulations on the IEEE 39-bus system. These simulations demonstrate the framework's capability to enhance detection accuracy by simplifying the locational FDIA detection challenge, achieved through strategic grid partitioning.

Original languageEnglish
Title of host publication4th International Conference on Smart Grid and Renewable Energy, SGRE 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350306262
DOIs
Publication statusPublished - 10 Jan 2024
Event4th International Conference on Smart Grid and Renewable Energy, SGRE 2024 - Doha, Qatar
Duration: 8 Jan 202410 Jan 2024

Publication series

Name4th International Conference on Smart Grid and Renewable Energy, SGRE 2024 - Proceedings

Conference

Conference4th International Conference on Smart Grid and Renewable Energy, SGRE 2024
Country/TerritoryQatar
CityDoha
Period8/01/2410/01/24

Keywords

  • Electrical functional strength
  • false data injection attack
  • power grid partition
  • smart grid cybersecurity

Fingerprint

Dive into the research topics of 'Enhanced Locational FDIA Detection in Smart Grids: A Scalable Distributed Framework'. Together they form a unique fingerprint.

Cite this