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A study on process information-driven cyber threat detection for I&C systems in NPP

Year: 2025
Type: article
Abstract: The increasing digitalization of Instrumentation and Control (I&C) systems in Nuclear Power Plants (NPPs) has improved operational efficiency while introducing cybersecurity vulnerabilities. Conventional network-based intrusion detection systems (IDS) face limitations in detecting sophisticated cyber threats targeting safety-critical controllers. To address these challenges, this study proposes a process information-driven cyber threat detection methodology based on real-time process data analysis and control logic consistency, enabling non-intrusive threat identification. The proposed methodology was examined through simulation and experimental testing using an APR-1400 Reactor Protection System (RPS) testbed. A cyber attack scenario targeting the High Pressurizer Pressure (HPP) Trip function was designed to assess the effectiveness of the detection mechanism. Simulation results demonstrated the detection algorithm's ability to identify unauthorized modifications to the trip setpoint, indicating the potential to detect cyber threats affecting reactor trip logic. Furthermore, experimental testing using the Safety Data Acquisition & Detection System (SDDS) demonstrated real-time anomaly detection while maintaining system integrity. These findings suggest that the proposed process-driven detection technique can enhance the cybersecurity resilience of NPPs without disrupting operational stability.
Authors: Jae Hwan Kim, Kwang Seop Son, Jae Gu Song, Yong Gu Lee, Young Jun Lee
Language: English
Open Access status: gold
Estimated APC paid: $200
OpenAlex ID: W7078252079
FWCI: 0.383
Cites: 7
Cited by: 1
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