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November 28, 2022 | Tom Ballard

ORNL researchers use blockchain technology to secure the electric grid

There’s a good deal of concern these days about hacking into everything from an individual’s health or financial records to the electric grid.

Now, thanks to the work of researchers at Oak Ridge National Laboratory (ORNL), blockchain, a technology best known for securing digital currency payments, has been used for the first time ever to validate communication among devices on the grid.

An ORNL research team led by Raymond Borges Hink is leading a project named the Darknet initiative for the U.S. Department of Energy’s Office of Electricity where the focus is on securing the nation’s electricity infrastructure by shifting its communications to increasingly secure methods.

As described in this ORNL news release, cyber risks have increased with two-way communication between grid power electronics equipment and new edge devices ranging from solar panels to electric car chargers and intelligent home electronics. By providing a trust framework for communication among electrical devices, the ORNL research team is increasing the resilience of the electric grid.

The team developed a framework to detect unusual activity, including data manipulation, spoofing and illicit changes to device settings. These activities could trigger cascading power outages as breakers are tripped by protection devices.

“This framework gives us a totally new capability to rapidly respond to anomalies,” Borges Hink said. “In the long run, we could more quickly identify an unauthorized system change, find its source and provide more trustworthy failure analysis. The goal is to limit the damage caused by a cyberattack or equipment failure.”

The approach uses tamper-resistant blockchain to spread configuration and operational data redundantly across multiple servers. The data and equipment settings are constantly verified against a statistical baseline of normal voltage, frequency, breaker status and power quality. Equipment settings are collected at frequent intervals and compared to the last good configuration saved in the blockchain. This allows rapid recognition of when and how settings were changed, whether those changes were authorized, and what caused them.