Pre-print: Radio Identity Verification-based IoT Security Using RF-DNA Fingerprints and SVM

TL;DR

This paper proposes a PHY layer IoT authentication method using RF-DNA fingerprints and SVMs, achieving perfect verification and attack rejection at moderate SNR levels, enhancing IoT security.

Contribution

It introduces a novel RF-DNA fingerprinting approach combined with SVMs for IoT device authentication, demonstrating high accuracy and robustness against spoofing attacks.

Findings

100% authorized ID verification at SNR ≥ 6 dB

Complete rejection of rogue spoofing at SNR ≥ 3 dB

Effective feature selection with Relief-F algorithm

Abstract

It is estimated that the number of IoT devices will reach 75 billion in the next five years. Most of those currently, and to be deployed, lack sufficient security to protect themselves and their networks from attack by malicious IoT devices that masquerade as authorized devices to circumvent digital authentication approaches. This work presents a PHY layer IoT authentication approach capable of addressing this critical security need through the use of feature reduced Radio Frequency-Distinct Native Attributes (RF-DNA) fingerprints and Support Vector Machines (SVM). This work successfully demonstrates 100%: (i) authorized ID verification across three trials of six randomly chosen radios at signal-to-noise ratios greater than or equal to 6 dB, and (ii) rejection of all rogue radio ID spoofing attacks at signal-to-noise ratios greater than or equal to 3 dB using RF-DNA fingerprints whose features are selected using the Relief-F algorithm.