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September 21, 2018

Electric grid protection through low-cost sensors, machine learning

Because virtually all industries and sectors rely upon electric power, the security of the electric grid often dominates cybersecurity discussions about critical infrastructure.

Researchers at the Department of Energy’s Lawrence Berkeley National Laboratory are already doing their part to secure the nation’s vulnerable electricity grids. They have developed a relatively low-cost method for on-the-fly detection of attacks on power grids.

Like some other researchers, the Berkeley team has focused on monitoring phasor measurement units (PMUs), sensors that are installed in fixed locations throughout the grid and send data about the status of the grid at a rate of 30 measurements per second to a control center.

“The idea is if we could leverage the physical behavior of components within the electrical grid, we could have better insight in terms of whether there was a cyberattack that sought to manipulate those components,” said Sean Peisert, a computer scientist in Berkeley Lab’s Computational Research Division and a cybersecurity expert. “These devices provide a redundant set of measurements that give us a high-fidelity way of tracking what is going on in the power distribution grid,” he said. Researchers can look at the measurements to detect anomalies, or they can compare the sensor readers with what the equipment reports to find discrepancies that could indicate  attacks against components in the power grid.

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