Cybersecurity for Energy Delivery Systems Projects

Berkeley Lab Computing Sciences Research is an active participant in a number of projects in the arena of cybersecurity for energy delivery systems.  Recently, this work has been funded largely via DOE’s Cybersecurity for Energy Delivery Systems (CEDS) R&D program. These projects include collaborations with academic, vendor, and utility partners. 

LBNL’s work in security for power grid control systems emphasizes both its historical role in developing, deploying and testing the Zeek (Bro) Network Security Monitor, as well as novel ideas that leverage and integrate physics — physical limitations, physical sensor output, and insight into commands sent to control systems — to help monitor and protect networked energy system devices under control.

Recent highlights of LBNL’s cybersecurity R&D activities include development of security monitoring systems for cyber-physical systems that integrate insights about the physical limitations of those systems into network security monitoring, that leverage high-resolution physical sensors combined with SCADA to identify cyberattacks on power grid distribution systems, and that enable automated response to attacks on solar inverters.

Some recent news:

CIGAR ‘Smokes Out’ Attacks on Solar Electrical Power Equipment — Jun. 7, 2021

Using Physics to Keep Our Electrical Grid Safe — Oct. 24, 2019

Impact of AI in DOE National Laboratories (YouTube video) (security discussion at 1'07") — Sept. 29, 2019

Solar power opens up new targets for cyber attackers (Archer News) — May 30, 2019

Cyberattacks threaten smart inverters, but scientists have solutions (Solar Power World) — April 30, 2019

CRD’s Peisert to Discuss Data Sharing at National Academies’ COSEMPUP Meeting — Nov. 5, 2018

Expert Q&A: Safeguarding the Nation’s Energy Infrastructure — Oct. 26, 2018

Electric grid protection through low-cost sensors, machine learning (GCN) — September 21, 2018

Cyber Defense Tool Is an Early Warning System for Grid Attacks (IEEE Spectrum Energywise Blog) — March 27, 2018

Older News

Key Representative Publications:

Nikhil Ravi, Anna Scaglione, Sachin Kadam, Reinhard Gentz, Sean Peisert, Brent Lunghino, Emmanuel Levijarvi, and Aram Shumavon, “Differentially Private K-means Clustering Applied to Meter Data Analysis and Synthesis,” IEEE Transactions on Smart Grid, June 17, 2022.

Ciaran Roberts Sy-Toan Ngo, Alexandre Milesi, Sean Peisert, Daniel Arnold, Shammya Saha, Anna Scaglione, Nathan Johnson, Anton Kocheturov, Dmitriy Fradkin, “Deep Reinforcement Learning for DER Cyber-Attack Mitigation,” Proceedings of the IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), November 11–13, 2020.

Mahdi Jamei, Raksha Ramakrishna, Teklemariam Tesfay, Reinhard Gentz, Ciaran Roberts, Anna Scaglione, and Sean Peisert, “Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization,” IEEE Journal on Selected Areas in Communications (J-SAC), Special Issue on Communications and Data Analytics in Smart Grid, accepted 2 October, 2019. [DOI]

Ciaran Roberts, Anna Scaglione, Mahdi Jamei, Reinhard Gentz, Sean Peisert, Emma M. Stewart, Chuck McParland, Alex McEachern, and Daniel Arnold, “Learning Behavior of Distribution System Discrete Control Devices for Cyber-Physical Security,” IEEE Transactions on Smart Grid, accepted 31 July, 2019. [DOI]

Melissa Stockman, Dipankar Dwivedi, Reinhard Gentz, Sean Peisert, “Detecting Programmable Logic Controller Code Using Machine Learning,” International Journal of Critical Infrastructure Protection, vol. 26, 100306, September 2019. (accepted July 3, 2019). [DOI]

Mahdi Jamei, Anna Scaglione, Ciaran Roberts, Emma Stewart, Sean Peisert, Chuck McParland, and Alex McEachern, “Anomaly Detection Using μPMU Measurements in Distribution Grids,” IEEE Transactions on Power Systems, 33(4), pp. 3611–3623, October 25, 2017. [DOI]

Mahdi Jamei, Emma Stewart, Sean Peisert, Anna Scaglione, Chuck McParland, Ciaran Roberts, and Alex McEachern, “Micro Synchrophasor-Based Intrusion Detection in Automated Distribution Systems: Towards Critical Infrastructure Security,” IEEE Internet Computing," 20(5), pp. 18-27, Sept./Oct. 2016. [DOI]

Chuck McParland, Sean Peisert, and Anna Scaglione, “Monitoring Security of Networked Control Systems: It’s the Physics,” IEEE Security and Privacy,12(6), November/December 2014. [BibTeX] [DOI]


A portion of the software developed through this project can be downloaded via Github.


Symbiosis in Byzantine Fault Tolerance and Intrusion Detection
This project was funded by NSF’s SaTC program, and was co-led by Sean Peisert. The theme of this effort was to integrate Byzantine fault tolerance (BFT) into intrusion detection systems (IDS), at both the fundamental and system levels, thereby improving both BFT and IDS. potential to improve BFT.