Towards Adaptive RF Fingerprint-based Authentication of IIoT devices

As IoT technologies mature, they are increasingly finding their way into more sensitive domains, such as Medical and Industrial IoT, in which safety and cyber-security are of great importance. While the number of deployed IoT devices continues to increase exponentially, they still present severe cyb...

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Bibliographic Details
Published inarXiv.org
Main Authors Lomba, Emmanuel, Severino, Ricardo, Ana Fernández Vilas
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 27.11.2023
Subjects
Authentication
Computer Science - Artificial Intelligence
Computer Science - Cryptography and Security
Cryptography
Cybersecurity
Fingerprinting
Industrial applications
Internet of Things
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Summary:As IoT technologies mature, they are increasingly finding their way into more sensitive domains, such as Medical and Industrial IoT, in which safety and cyber-security are of great importance. While the number of deployed IoT devices continues to increase exponentially, they still present severe cyber-security vulnerabilities. Effective authentication is paramount to support trustworthy IIoT communications, however, current solutions focus on upper-layer identity verification or key-based cryptography which are often inadequate to the heterogeneous IIoT environment. In this work, we present a first step towards achieving powerful and flexible IIoT device authentication, by leveraging AI adaptive Radio Frequency Fingerprinting technique selection and tuning, at the PHY layer for highly accurate device authentication over challenging RF environments.
ISSN:2331-8422
DOI:10.48550/arxiv.2311.15888