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Detecting the Exploitation of Hardware Vulnerabilities using Electromagnetic Emanations
  • Giancarlo Canales Barreto ,
  • Nicholas Lamb
Giancarlo Canales Barreto
Battelle Memorial Institute

Corresponding Author:[email protected]

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Nicholas Lamb
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Abstract

We present a cache attack monitoring methodology that leverages statistical machine learning models to detect n-day hardware attacks by analyzing the electromagnetic emanations of a device. Experimental results from a Raspberry Pi 4 hosting Linux and a Jetson TX2 development board running a Linux guest hosted by seL4 demonstrate that our approach can sense Spectre attacks with a concordance statistic of 97% and 95%.