RT25 | Validating Cloud-Based Detection of False Data Injection Attacks Using OPAL-RT and Edge Devices

Sunho Jang from Brookhaven National Laboratory presents a neural-network-based method to detect False Data Injection Attacks (FDIAs) in virtual power plants. Leveraging OPAL-RT simulations and edge devices, the study validates a cloud-integrated cybersecurity testbed, using correlation-reconstruction autoencoders to enhance DER resilience and ensure secure, real-time data processing in distributed grid environments.