Radio Identity Verification-Based IoT Security Using RF-DNA Fingerprints and SVM

Abstract

It is estimated that the number of Internet-of-Things (IoT) devices will reach 75 billion in the next five years. Most of those currently and soon-to-be deployed devices lack sufficient security to protect themselves and their networks from attacks by malicious IoT devices masquerading as authorized devices in order to circumvent digital authentication approaches. This work presents a physical (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: 1) authorized identity (ID) verification across three trials of six randomly chosen radios at signal-to-noise ratios greater than or equal to 6 dB and 2) 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.