FIDS: A Federated Intrusion Detection System for 5G Smart Metering Network

Parya Haji Mirzaee, Mohammad Shojafar, Zahra Pooranian, Pedram Asef, Haitham Cruickshank, Rahim Tafazolli

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

13 Citations (SciVal)

Abstract

In a critical infrastructure such as Smart Grid (SG), providing security of the system and privacy of consumers are significant challenges to be considered. The SG developers adopt Machine Learning (ML) algorithms within the Intrusion Detection System (IDS) to monitor traffic data and network performance. This visibility safeguards the SG from possible intrusions or attacks that may trigger the system. However, it requires access to residents' consumption information which is a severe threat to their privacy. In this paper, we present a novel method to detect abnormalities on a large scale SG while preserving the privacy of users. We design a Federated IDS (FIDS) architecture using Federated Learning (FL) in a 5G environment for the SG metering network. In this way, we design Federated Deep Neural Network (FDNN) model that protects customers' information and provides supervisory management for the whole energy distribution network. Simulation results for a real-time dataset demonstrate the reasonable improvement of the proposed FDNN model compared with the state-of-the-art algorithms. The FDNN achieves approximately 99.5% accuracy, 99.5% precision/recall, and 99.5% f1-score when comparing with classification algorithms.

Original languageEnglish
Title of host publicationProceedings - 2021 17th International Conference on Mobility, Sensing and Networking, MSN 2021
PublisherIEEE
Pages215-222
Number of pages8
ISBN (Electronic)9781665406680
DOIs
Publication statusPublished - 2021
Event17th International Conference on Mobility, Sensing and Networking, MSN 2021 - Virtual, Exeter, UK United Kingdom
Duration: 13 Dec 202115 Dec 2021

Publication series

NameProceedings - 2021 17th International Conference on Mobility, Sensing and Networking, MSN 2021

Conference

Conference17th International Conference on Mobility, Sensing and Networking, MSN 2021
Country/TerritoryUK United Kingdom
CityVirtual, Exeter
Period13/12/2115/12/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

  • 5G
  • Advanced Metering Infrastructure (AMI)
  • Federated Learning (FL)
  • Intrusion Detection System (IDS)
  • Network Security
  • Smart Grid (SG)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management

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