# Scanning the Cycle: Timing-based Authentication on PLCs

arXiv: https://arxiv.org/abs/2102.08985 · HTML: https://mlsanity.com/paper/2102.08985/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Feb 2021.

## Built on by (most cited first, 4 of 4)

- [Attack Rules: An Adversarial Approach to Generate Attacks for Industrial Control Systems using Machine Learning](https://mlsanity.com/paper/2107.05127/) (2021)
- [AttackLLM: LLM-based Attack Pattern Generation for an Industrial Control System](https://mlsanity.com/paper/2504.04187/) (2025)
- [Code Integrity Attestation for PLCs using Black Box Neural Network Predictions](https://mlsanity.com/paper/2106.07851/) (2021)
- [Attack Pattern Mining to Discover Hidden Threats to Industrial Control Systems](https://mlsanity.com/paper/2508.04561/) (2025)

## 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.