Introduction of Gabor Transform Features for an Internet of Things Security Paradigm

Abstract

As the proliferation of Internet of Things (IoT) devices spreads across critical infrastructure sectors, the threat likewise increases as attack vectors become proportionally more serious. It is necessary to balance protection complexity and operational disruption while providing resilient and effective security solutions. Distinct Native Attribute (DNA) fingerprinting using RF Signal Gabor transform (GTX) features has proven to be computationally inexpensive and robust in physical (PHY) layer applications. This work combines GTX discrimination gains with data dimensional reduction using GTX-derived images to achieve effective DNA fingerprinting—this is done using lower-dimensional images of Radio Frequency (RF) signal Gabor transform responses to perform Image Domain DNA (ID-DNA) Fingerprinting. ID-DNA Fingerprinting performance includes accurate device classification of %C = 90% and reliable detection of rogue devices at a Rogue Rejection Rate (RRR) of RRR = 90%.