Open Access

ARTICLE

Hardware-Enabled Key Generation in Industry 4.0 Cryptosystems through Analog Hyperchaotic Signals

Borja Bordel Sánchez^1,*, Fernando Rodríguez-Sela¹, Ramón Alcarria², Tomás Robles¹

1 IT Department, Universidad Politécnica de Madrid, Madrid, 28031, Spain
2 Department of Geospatial Engineering, Universidad Politécnica de Madrid, Madrid, 28031, Spain

* Corresponding Author: Borja Bordel Sánchez. Email:

Computers, Materials & Continua 2025, 83(2), 1821-1853. https://doi.org/10.32604/cmc.2025.059012

Received 26 September 2024; Accepted 24 January 2025; Issue published 16 April 2025

Abstract

The Industry 4.0 revolution is characterized by distributed infrastructures where data must be continuously communicated between hardware nodes and cloud servers. Specific lightweight cryptosystems are needed to protect those links, as the hardware node tends to be resource-constrained. Then Pseudo Random Number Generators are employed to produce random keys, whose final behavior depends on the initial seed. To guarantee good mathematical behavior, most key generators need an unpredictable voltage signal as input. However, physical signals evolve slowly and have a significant autocorrelation, so they do not have enough entropy to support high-randomness seeds. Then, electronic mechanisms to generate those high-entropy signals artificially are required. This paper proposes a robust hyperchaotic circuit to obtain such unpredictable electric signals. The circuit is based on a hyperchaotic dynamic system, showing a large catalog of structures, four different secret parameters, and producing four high entropy voltage signals. Synchronization schemes for the correct secret key calculation and distribution among all remote communicating modules are also analyzed and discussed. Security risks and intruder and attacker models for the proposed solution are explored, too. An experimental validation based on circuit simulations and a real hardware implementation is provided. The results show that the random properties of PRNG improved by up to 11% when seeds were calculated through the proposed circuit.

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Keywords

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