  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.
