Open Access

ARTICLE

Root Security Parameter Generation Mechanism Based on SRAM PUF for Smart Terminals in Power IoT

Xiao Feng^1,2,3,*, Xiao Liao^1,3, Xiaokang Lin^1,3, Yonggui Wang^1,3

1 Information and Communication Research Institute, State Grid Information Telecommunication Group Co., Ltd., Beijing, 102211, China
2 School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, 100876, China
3 Smart IoT Business Unit, State Grid Info-Telecom Great Power Science and Technology Co., Ltd., Xiamen, 361008, China

* Corresponding Author: Xiao Feng. Email:

Computers, Materials & Continua 2025, 83(1), 1307-1325. https://doi.org/10.32604/cmc.2025.061069

Received 16 November 2024; Accepted 07 February 2025; Issue published 26 March 2025

Abstract

In the context of the diversity of smart terminals, the unity of the root of trust becomes complicated, which not only affects the efficiency of trust propagation, but also poses a challenge to the security of the whole system. In particular, the solidification of the root of trust in non-volatile memory (NVM) restricts the system’s dynamic updating capability, which is an obvious disadvantage in a rapidly changing security environment. To address this issue, this study proposes a novel approach to generate root security parameters using static random access memory (SRAM) physical unclonable functions (PUFs). SRAM PUFs, as a security primitive, show great potential in lightweight security solutions due to their inherent physical properties, low cost and scalability. However, the stability of SRAM PUFs in harsh environments is a key issue. These environmental conditions include extreme temperatures, high humidity, and strong electromagnetic radiation, all of which can affect the performance of SRAM PUFs. In order to ensure the stability of root safety parameters under these conditions, this study proposes an integrated approach that covers not only the acquisition of entropy sources, but also the implementation of algorithms and configuration management. In addition, this study develops a series of reliability-enhancing algorithms, including adaptive parameter selection, data preprocessing, auxiliary data generation, and error correction, which are essential for improving the performance of SRAM PUFs in harsh environments. Based on these techniques, this study establishes six types of secure parameter generation mechanisms, which not only improve the security of the system, but also enhance its adaptability in variable environments. Through a series of experiments, we verify the effectiveness of the proposed method. Under 10 different environmental conditions, our method is able to achieve full recovery of security data with an error rate of less than 25%, which proves the robustness and reliability of our method. These results not only provide strong evidence for the stability of SRAM PUFs in practical applications, but also provide a new direction for future research in the field of smart terminal security.

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Keywords

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