Scanning the Cycle: Timing-based Authentication on PLCs
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Abstract (arXiv)
Programmable Logic Controllers (PLCs) are a core component of an Industrial Control System (ICS). However, if a PLC is compromised or the commands sent across a network from the PLCs are spoofed, consequences could be catastrophic. In this work, a novel technique to authenticate PLCs is proposed that aims at raising the bar against powerful attackers while being compatible with real-time systems. The proposed technique captures timing information for each controller in a non-invasive manner. It is argued that Scan Cycle is a unique feature of a PLC that can be approximated passively by observing network traffic. An attacker that spoofs commands issued by the PLCs would deviate from such fingerprints. To detect replay attacks a PLC Watermarking technique is proposed. PLC Watermarking models the relationship between the scan cycle and the control logic by modeling the input/output as a function of request/response messages of a PLC. The proposed technique is validated on an operational water treatment plant (SWaT) and smart grid (EPIC) testbed. Results from experiments indicate that PLCs can be distinguished based on their scan cycle timing characteristics.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Feb 2021.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 0; 2024: 0; 2025: 2.
4 papers.
- 2021Attack Rules: An Adversarial Approach to Generate Attacks for Industrial Control Systems using Machine Learningcited by 5
- 2025AttackLLM: LLM-based Attack Pattern Generation for an Industrial Control Systemcited by 4
- 2021Code Integrity Attestation for PLCs using Black Box Neural Network Predictionscited by 0
- 2025Attack Pattern Mining to Discover Hidden Threats to Industrial Control Systemscited by 0
- 2025Attack Pattern Mining to Discover Hidden Threats to Industrial Control Systems6 Aug 2025
- 2025AttackLLM: LLM-based Attack Pattern Generation for an Industrial Control System5 Apr 2025
- 2021Attack Rules: An Adversarial Approach to Generate Attacks for Industrial Control Systems using Machine Learning11 Jul 2021
- 2021Code Integrity Attestation for PLCs using Black Box Neural Network Predictions15 Jun 2021
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Close in wording, no citation either way
- 2026PLCBench: Can Autonomous LLM Agents Turn PLC Access into Sustained Physical Impact?
- 2024Simple Cracking of (Noise-Based) Dynamic Watermarking in Smart Grids ↗
- 2022Attack Detection for Networked Control Systems Using Event-Triggered Dynamic Watermarking ↗
- 2022Hardware Watermarking for Finite State Machines, with Symmetric Circuit Encryption ↗
- 2024Delay-Induced Watermarking for Detection of Replay Attacks in Linear Systems ↗
- 2024Agents4PLC: Automating Closed-loop PLC Code Generation and Verification in Industrial Control Systems using LLM-based Agents
- 2026Kerckhoffs-Compliant Watermarking for Physical Design IP Protection: From Placement to Routing ↗
- 2025DynaMark: A Reinforcement Learning Framework for Dynamic Watermarking in Industrial Machine Tool Controllers