Artificial Intelligence for Energy Systems Cybersecurity

Conference · Thu Oct 07 00:00:00 EDT 2021

OSTI ID:1825677

Macwan, Richard; King, Ryan

Artificial intelligence and machine learning systems have the potential to influence the future design and implementation of cybersecurity systems for the power grid. These systems may enhance the overall operation of the power system by leveraging and making sense of massive amounts of data. However, we must also understand how AI/ML will need to be protected from cyber threat actors. We discuss the existing insights the NREL team has developed using AI/ML systems and then present resources including ESIF and the Cyber Energy Emulation Platform that can be used to generate training data and insights. We end by offering suggestions on priority research paths for AI in cybersecurity.

• Research Organization: National Renewable Energy Lab. (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE National Renewable Energy Laboratory (NREL), Energy Security and Resilience Center
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1825677
• Report Number(s): NREL/PR-5R00-81098; MainId:79874; UUID:32c4d2b5-e8f5-47be-8544-99a99b52aa16; MainAdminID:63144
• Resource Relation: Conference: Presented at the Artificial Intelligence Summit Cyber Security Grand Challenge, 29 September 2021
• Country of Publication: United States
• Language: English

Related Subjects

POWER TRANSMISSION AND DISTRIBUTION
artificial intelligence
autoencoders
cyber-energy emulation platform
cybersecurity
deep reinforcement learning
distributed denial-of-service
distribution utility emulation environment
EPRI
hybrid intrusion detection
intrusion detection systems
machine learning
research opportunities
resilience