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Decentralized Correlation and Mitigation of Cyberattacks on Distribution Systems | IEEE Conference Publication | IEEE Xplore

Decentralized Correlation and Mitigation of Cyberattacks on Distribution Systems


Abstract:

As the power grid is a cyber-physical system, it is vulnerable to cyberattacks. Therefore, research on the cyberse-curity of the grid is in critical need. In response to ...Show More

Abstract:

As the power grid is a cyber-physical system, it is vulnerable to cyberattacks. Therefore, research on the cyberse-curity of the grid is in critical need. In response to this, research has been focused on the various cybersecurity issues of the grid, including the formulation of cybersecurity frameworks. However, it is noteworthy that a significant proportion of the literature is concerned with centralized mechanisms, which are prone to single point failures. The literature also appears focused on the transmission system, so that certain solutions are impracticable at the distribution level. In this paper, a cybersecurity architecture is proposed for the electric energy distribution system. The proposed method is a decentralized mechanism for attack correlation and mitigation. A prototype of the proposed architecture is also presented, simulations of which are performed using the IEEE 13-Node Test Feeder. The simulations have validated the performance of the prototype, and consequently the advantage of the proposed architecture.
Date of Conference: 18-21 October 2021
Date Added to IEEE Xplore: 21 December 2021
ISBN Information:
Conference Location: Espoo, Finland

I. Introduction

Power systems today are cyber-physical critical infrastructure. As such, there may be severe consequences for both utilities and customers alike when persons with malicious intent gain access to the grid. The electric power grid has therefore been the subject of both cyberattacks and cybersecurity research. Research on the cybersecurity issues of the power grid is wide-ranged and tackle issues such as vulnerability assessment, attack detection, correlation, and mitigation.

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References

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