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Author:

Li, Hongchen (Li, Hongchen.) | Tu, Shanshan (Tu, Shanshan.) | Li, Wenlong (Li, Wenlong.) | Yue, Qingqing (Yue, Qingqing.) | Ai, Xin (Ai, Xin.)

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CPCI-S EI Scopus

Abstract:

In the rapidly expanding realm of the Industrial Internet of Things (IIoT), safeguarding sensitive data against sophisticated cyber threats has become critical. The complexity of traditional cryptographic solutions often exceeds the limited computational capabilities of IIoT devices. To address this, we propose the Robust 5G Authentication Framework for Industrial IoT (RAFII-RDP), a framework engineered to withstand the unique challenges posed by desynchronization attacks in industrial contexts. Distinguishing itself from contemporary lightweight cryptographic approaches, RAFII-RDP integrates a secure hash function with XOR encryption to significantly reduce cryptographic burdens, making it apt for devices with limited resources. Central to our scheme is the utilization of Physical Unclonable Functions (PUFs) to generate distinctive, device-specific signatures that bolster data security while obviating the need for centralized verification systems. Comparative analysis reveals that RAFII-RDP achieves a 34% reduction in memory usage for sensors and a 27% reduction for routers when measured against the Esfahani protocol. Beyond its resilience to state misalignments, our protocol enhances user privacy and data integrity, propelling us toward a more secure and robust IIoT infrastructure. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keyword:

5G mobile communication systems Authentication Protocol Authentication Cryptography Cyber attacks Data privacy

Author Community:

  • [ 1 ] [Li, Hongchen]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Tu, Shanshan]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 3 ] [Li, Wenlong]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 4 ] [Yue, Qingqing]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 5 ] [Ai, Xin]Faculty of Information Technology, Beijing University of Technology, Beijing, China

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ISSN: 2211-0984

Year: 2025

Volume: 175 MMS

Page: 35-48

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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