Work

FANCY-X: A nuclear power plant network testbed for cross-network cybersecurity evaluation and generalizability

Year: 2026

Type: article

Abstract: With the proliferation of digital technologies in instrumentation and control systems comes an increased demand for improvements in cybersecurity. Developing strategies for preventing and detecting cyber-attacks is important in safety-critical systems such as nuclear power plants (NPPs). The application of machine learning (ML) to automate cyber-attack detection on operational technology (OT) networks is increasing significantly. To help facilitate the development of ML algorithms for cyber-attack detection, it is necessary to develop testbeds that are representative of the target networks on which the algorithms will be deployed. However, the design of cyber-attack detection methods using data from a specific network testbed can result in models that achieve high performance on that network but do not generalize well to others. The design of cyber-attack detection algorithms for NPP networks that are generalizable across networks is therefore essential to avoid significant performance degradation as well as to minimize disruptive testing on a target physical plant and improve the generalization. To solve this challenge, an NPP cybersecurity testbed called FANCY-X is developed, which is composed of two disjoint networks. One is entirely virtual, while the other is a hybrid network containing both virtual and physical components that emulate an NPP network. Cyber-attack detection cross-network generalizability can be evaluated by training on the virtual network and testing on the hybrid network. A high-fidelity two-loop pressurized water reactor (PWR) simulator is used to represent the underlying NPP, enabling the generation of realistic network activity. The FANCY-X testbed is validated through both same-network and cross-network evaluations.

Source: Progress in Nuclear Energy

DOI: 10.1016/j.pnucene.2026.106444

Authors: Marc Zebrowitz, Michael A. Doran, Fan Zhang

Institution: Georgia Institute of Technology

Language: English

Topic: Smart Grid Security and Resilience

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,930