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https://doi.org/10.5772/intech...
Part of book or chapter of book . 2025 . Peer-reviewed
License: CC BY
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Hardware Reverse Engineering for Secure Smart Grids

Authors: Arne Roar Nygård; Arvind Sharma; Sokratis Katsikas;

Hardware Reverse Engineering for Secure Smart Grids

Abstract

Industry 5.0 and smart grid technologies are mutually dependent and synergistic. They complement each other by leveraging advanced digital capabilities to enhance energy efficiency, integrate renewable energy sources, and improve the resilience and reliability of industrial operations and electricity distribution systems. With the mounting threat of cyberattacks targeting digital supply chains, including those of the smart grid, it is evident that vendors, service providers, and outsourced Information and Communication Technology (ICT) providers face equal susceptibility to exploitation by malicious actors. Since all security measures hinge on dependable hardware, comprehending the origins of hardware vulnerabilities in Intelligent Electronic Devices (IEDs), a key component in smart grid systems, is imperative. Given the extended nature of digital supply chains, often involving components from various manufacturers, it is equally important to adopt novel approaches and methodologies to verify that IEDs are as secure as required. Integrating a Hardware Reverse Engineering business subprocess into the equipment procurement process offers a promising avenue for enhancing the cybersecurity and the cyber resilience of the digital supply chain of smart grid operators. This chapter proposes such a process and outlines a use case involving a specific IED commonly employed in digital substations in the smart grid.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid