A Deep Learning Approach To Iot Authentication

At its peak, the Internet-of-Things will largely be composed of low-power devices with wireless radios attached. Yet, secure authentication of these devices amidst adversaries with much higher power and computational capability remains a challenge, even for advanced cryptographic and wireless security protocols. For instance, a high-power software radio could simply replay chunks of signals from a low-power device to emulate it.This paper presents a deep-learning based classifier that learns hardware imperfections of low-power radios that are challenging to emulate, even for high-power adversaries. We build an LSTM framework, specifically sensitive to signal imperfections that persist over long durations. Experimental results from a testbed of 30 low-power nodes demonstrates high resilience to advanced software radio adversaries.