A Secure Online Fingerprint Authentication System for Industrial IoT Devices over 5G Networks
Article
Bedari, Aseel, Wang, Song and Yang, Wencheng. 2022. "A Secure Online Fingerprint Authentication System for Industrial IoT Devices over 5G Networks." Sensors. 22 (19), pp. 1-16. https://doi.org/10.3390/s22197609
| Article Title | A Secure Online Fingerprint Authentication System for Industrial IoT Devices over 5G Networks |
|---|---|
| ERA Journal ID | 34304 |
| Article Category | Article |
| Authors | Bedari, Aseel (Author), Wang, Song (Author) and Yang, Wencheng (Author) |
| Journal Title | Sensors |
| Journal Citation | 22 (19), pp. 1-16 |
| Article Number | 7609 |
| Number of Pages | 16 |
| Year | 2022 |
| Publisher | MDPI AG |
| Place of Publication | Switzerland |
| ISSN | 1424-8220 |
| 1424-8239 | |
| Digital Object Identifier (DOI) | https://doi.org/10.3390/s22197609 |
| Web Address (URL) | https://www.mdpi.com/1424-8220/22/19/7609 |
| Abstract | The development of 5G networks has rapidly increased the use of Industrial Internet of Things (IIoT) devices for control, monitoring, and processing purposes. Biometric-based user authentication can prevent unauthorized access to IIoT devices, thereby safeguarding data security during production. However, most biometric authentication systems in the IIoT have no template protection, thus risking raw biometric data stored as templates in central databases or IIoT devices. Moreover, traditional biometric authentication faces slow, limited database holding capacity and data transmission problems. To address these issues, in this paper we propose a secure online fingerprint authentication system for IIoT devices over 5G networks. The core of the proposed system is the design of a cancelable fingerprint template, which protects original minutia features and provides privacy and security guarantee for both entity users and the message content transmitted between IIoT devices and the cloud server via 5G networks. Compared with state-of-the-art methods, the proposed authentication system shows competitive performance on six public fingerprint databases, while saving computational costs and achieving fast online matching. |
| Keywords | 5G network; cancelable fingerprint template; fingerprint authentication; IIoT; secure authentication |
| ANZSRC Field of Research 2020 | 460403. Data security and protection |
| Byline Affiliations | La Trobe University |
| School of Mathematics, Physics and Computing | |
| Institution of Origin | University of Southern Queensland |
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