Implementation of a Trust-Based Framework for Substation Defense in the Smart Grid

Author:

Boakye-Boateng Kwasi1ORCID,Ghorbani Ali A.1ORCID,Lashkari Arash Habibi2ORCID

Affiliation:

1. Canadian Institute for Cybersecurity (CIC), Faculty of Computer Science, University of New Brunswick (UNB), Fredericton, NB E3B 5A3, Canada

2. Behaviour-Centric Cybersecurity Centre, School of Information Technology, York University, Toronto, ON M3J 1P3, Canada

Abstract

The Smart Grid is a cyber-integrated power grid that manages electricity generation, transmission, and distribution to consumers and central to its functioning is the substation. However, integrating cyber-infrastructure into the substation has increased its attack surface. Notably, sophisticated attacks such as the PipeDream APT exploit multiple device protocols, such as Modbus, DNP3, and IEC61850. The substation’s constraints pose challenges for implementing security measures such as encryption and intrusion detection systems. To address this, we propose a comprehensive trust-based framework aimed at enhancing substation security. The framework comprises a trust model, a risk posture model, and a trust transferability model. The trust model detects protocol-based attacks on Intelligent Electronic Devices and SCADA HMI systems, while the risk posture model dynamically assesses the substation’s risk posture. The trust transferability model evaluates the feasibility of transferring and integrating a device and its trust capabilities into a different substation. The practical substation emulation involves a Docker-based testbed, employing a multi-agent architecture with a real-time Security Operations Center-influenced dashboard. Assessment involves testing against attacks guided by the MITRE ICS ATT&CK framework. Our framework displays resilience against diverse attacks, identifies malicious behavior, and rewards trustworthy devices.

Funder

Atlantic Canada Opportunities Agency

Natural Sciences and Engineering Research Council of Canada

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Urban Studies

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