Towards federated learning-based collaborative adaptive cybersecurity for multi-microgrids

Svetlana Boudko, Habtamu Abie, Ethiopia Nigussie, Reijo Savola

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

Abstract

Multi-microgrids (MMGs) provide economic and environmental benefits to society by improving operational flexibility, stability and reliability of a smart grid. MMGs have greater complexity than conventional power networks due to the use of multiple infrastructures, communication protocols, controllers, and intelligent electronic devices. The distributed and heterogeneous connectivity technologies of the MMGs and their need to exchange information with external sources as well as the vulnerabilities in the communication networks and software-based components, make MMGs susceptible to cyberattacks. In this work, we present a conceptual framework for collaborative adaptive cybersecurity that is able to proactively detect security incidents. The framework utilizes federated learning for collaborative training of shared prediction models in a decentralized manner. The methodology used in this research is mainly analytical. This involves analysis of how the principles of a collaborative adaptive cybersecurity can be applied to the MMG environments resulting in the development of theoretical models which can then be validated in practice by prototyping and using real time simulation.

Original languageEnglish
Title of host publicationProceedings of the 18th International Conference on Wireless Networks and Mobile Systems, WINSYS 2021
EditorsJoel Rodrigues, Joel Rodriguesl, Jaime Lloret Mauri
PublisherSciTePress
Pages83-90
ISBN (Electronic)978-989-758-529-6
DOIs
Publication statusPublished - 2021
MoE publication typeA4 Article in a conference publication
Event18th International Conference on Wireless Networks and Mobile Systems, WINSYS 2021 - Virtual, Online
Duration: 7 Jul 20219 Jul 2021

Conference

Conference18th International Conference on Wireless Networks and Mobile Systems, WINSYS 2021
CityVirtual, Online
Period7/07/219/07/21

Keywords

  • Adaptive Mechanisms
  • Collaborative Protocols
  • Cybersecurity
  • Federated Learning
  • Machine Learning
  • Multi-microgrid

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