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Electronics· 2026Q2

A Digital Twin-Based Fuzzing Framework for Cyber–Physical Security Verification in Operational Technology Systems

Minako Toba, Ashokkumar Chettymani, Mayuko Tanaka, Satoshi Misaka et al.

Short summary

A novel digital twin-based fuzzing framework detects protocol-valid cyber-physical security vulnerabilities in Operational Technology (OT) systems by monitoring the physical process state, not just communication anomalies.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Proposes a digital twin-based fuzzing framework for OT systems, integrating sensor, PLC, and actuator emulation.
  • Employs a physical-state oracle to judge test inputs based on the true state of the physical process, not just communication responses.
  • Prototype achieved response latency < 100 ms and anomaly detection within 1 s in basic operational checks.
  • Detected 57 failures in a turbine startup controller, including safety violations from stuck sensor readings and controller weaknesses, none of which produced communication or software anomalies.

AI-generated from the title and abstract; the full text is not read.

Abstract

Operational Technology (OT) systems are increasingly exposed to cybersecurity threats. Fuzzing is effective for vulnerability discovery, but conventional fuzzers judge test outcomes from crashes or protocol responses and cannot detect protocol-valid inputs that drive the physical process into an unsafe state; testing production OT systems is also risky. This paper proposes a digital twin-based fuzzing framework that integrates sensor emulation, PLC logic emulation, actuator emulation, monitoring, and fuzz testing, and judges each test input with a physical-state oracle that computes the true state of the process. A prototype based on Modbus and WebSocket communications was evaluated in two steps. A basic operational check showed response latency below 100 ms, 100% output consistency, and anomaly detection within 1 s. A quantitative experiment on a thermal power plant-inspired turbine startup controller, with 117 valid trials under four conditions, detected 57 failures, none of which produced a communication or software anomaly. Stuck sensor readings caused safety violations, an injected input-validation defect was exposed in every valid trial, and two unintended weaknesses in the controller’s plausibility check were revealed. These results indicate that fuzzing results in OT systems should be judged from the physical state of the process and that digital twins provide a practical platform for doing so.

The authors' abstract, as published at the source. Electronics, 2026 · DOI ↗

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Field: Software

SoftwareComputer Science