A New Way to Detect Cyberattacks: Extracting Changes in Register Values from Radio-Frequency Side Channels

Abstract

The Internet of Things (IoT) and the Internet of Everything (IoE) have driven processors into nearly every powered device, from thermostats to refrigerators to light bulbs. From a security perspective, the IoT and IoE create a new layer of signals and systems that can provide insight into the internal operations of a device via analog side channels. Our research focuses on leveraging these analog side channels in IoT/IoE processors to detect intrusions. Our goal is to defend against cyberattacks that insert malware into IoT devices by detecting deviations in the code running on their processors from known firmware. Our approach applies signal processing and machine-learning techniques to collected radio-frequency (RF) emissions of code running on the processor.